Praca Dyplomowa - Photogrammetry and Remote Sensing - AGH

Praca Dyplomowa 

Temat pracy: Badanie metod dotyczących tworzenia szczegółowych modeli 

cyfrowych rzeźb i innych obiektów 

Title of work: Investigation on methods for making detailed digital models 

of sculptures and other artefacts 

Oppgave tittel: Undersøkelse av metoder for å lage detaljerte digitale 

modeller av skulpturer og andre objekter 

Nazwisko i imię: Małgorzata Aulejtner 

Kierunek studiów: Geodezja i Kartografia 

Specjalność: Geoinformacja, Fotogrametria i Teledetekcja 

Ocena:…………… 

Akademia Górniczo-Hutnicza 

Im. Stanisława Staszica w Krakowie 

Wydział Geodezji Górniczej 

i Inżynierii Środowiska 

Katedra Geoinforamcji, Fotogrametrii 

i Teledetekcji Środowiska 

Recenzent: Opiekun Pracy: 

Dr inż. Sławomir Mikrut dr hab. inż. Regina Tokarczyk 

Oświadczam, świadomy(a) odpowiedzialności karnej za poświadczenie nieprawdy, że 

niniejszą pracę dyplomową wykonałem(am) osobiście i samodzielnie i że nie 

korzystałem(am) ze źródeł innych niż wymienione w pracy. 

........................................... 

czytelny podpis autora pracy 

Kraków 2011

Streszczenie pracy : 

Różnego rodzaju rzeźby i inne artefakty dorobku kulturalnego są narażone na zniszczenia, 

które czasem trudno uniknąć. Tworzy się więc nowe repliki tych obiektów w celu ochrony 

tego dziedzictwa. Aby uniknąć dodatkowych zniszczeń w czasie wykonywania tych kopii, 

odchodzi się od dawnych metod – wykonywanych metodą odlewów. Stosuje się więc tutaj 

metody jak trójwymiarowe skanowanie za pomocą skanera lub metody fotogrametryczne, w 

których nie trzeba dotykać w żaden sposób obiektu dzięki czemu ewentualne zniszczenia są 

minimalizowane. Trójwymiarowe digitalne modele utrzymane z nowszych metod mogą być 

użyte następnie do utworzenia realnej repliki przy zastosowaniu specjalistycznych drukarek 

trójwymiarowych, które “wyrzeżbią” dany obiekt. 

Celem tej pracy było badanie bezdotykowych, nowszych metod tworzenia szczegółowych 

modeli 3D na przykładzie rzeźby z katedry Nidaros w Trondheim (Norwegia). Głównym 

priorytetem było uzyskanie jak najbardziej dokładnego modelu, przede wszystkim aby 

uzyskać jak najwięcej szczegółów. W pracy mieści się więc porównanie metod 

fotogrametrycznych, skaningu a także narzędzi do modelowania 3D. 

Do uzyskania modelu z dużą ilością małych szczegółów rzeźby użytej w projekcie potrzebna 

jest duża chmura punktów. Trzeba zwrócić uwagę, iż rzeźba nie była płaska, a dość okrągła, 

złożona z różnych powierzchni z wieloma małymi obiektami. Uzyskana chmura punktów 

powinna być więc tutaj bardzo dokładna z wysoką rozdzielczością. Nie mniej jednak, takie 

parametry powodują iż niemalże każdy program potrzebuje dość dużo czasu aby obliczyć tak 

dużo danych, czy to z metody fotogrametrycznej czy też skaningu. Głównie nie jest to jednak 

spowodowane słabymi parametrami używanego komputera, ale ograniczeniami programów. 

Na rynku dostępne są różne skanery, są jednak i takie które potrafią uzyskać bardzo gęstą 

chmurę punktów a dużą dokładnością. Zazwyczaj, jeżeli skaner jest stworzony do skanowania 

mały obiektów z bliska a rozdzielczość i dokładność rośnie, są one coraz mniejsze w 

rozmiarze. Im większa dokładność tym mniejszy zasięg również, tak więc dla mniejszych 

obiektów – mniejsza odległość skanowania jest zalecana. Metody fotogrametryczne również 

mogą dać dobre wyniki i dobrą rozdzielczość, jednak tylko w momencie gdy materiał 

fotografowanego obiektu nie świeci się, nie odbija światła ani nie jest ze szkła. 

W projekcie zostały wykorzystane następujące fotogrametryczne programy: PhotoModeler 

Scanner i Topcon ImageMaster. Są to dość podobne programy, gdzie obydwa potrafią 

stworzyć powierzchnie trójwymiarowe używając do tego zdjęć zrobionych kamerą 

niemetryczną. Obydwie firmy zapewniają również kalibrację takiej kamery. Resultat z tych 

programów jest dość dobry, jednak powierzchnia rzeźby świeciła się nieco i było widać 

refleksy, odbicie światła w niektórych miejscach na zdjęciu, przez co matching i generacja 

punktów 3D nie działała w tym wypadku najlepiej. Powyższe problemy resultowały na 

modelu w ten sposób, iż widoczny był szum, źle obliczone punkty – odstrzelone od modelu. 

Ponadto, czas potrzebny do obliczenia i wygenerowania DSM był dość długi i to przede 

wszystkim powinno zostać wzięte pod uwagę przy dalszym ulepszaniu programów. 

Oprócz wymienionych programów, aplikacja Autodesk – Project Photofly 2.0 była również 

testowana. Program jest w stanie wygenerować teksturowany mesh – powierzchnię TIN 3D. 

Jest to program freewere, dostępny na stronie Autodesk do ściągnięcia i jest bardzo łatwy w 

obsłudze – użytkownicy bez znajomości fotogrametrii będą w stanie bez problemu wykonać 

model. Jednakże, program nie jest w stanie wykonać tak dokładnego modelu jak wspomniane 

ii

wcześniej aplikacje. Nie mniej jednak, w wielu sytuacjach może to wystarczyć i dać dużo 

możliwości. 

Ze skaningu w projekcie został użyty skaner Konica Minolta VI-910, ale także bardzo 

ciekawy, mały, przenośny skaner Artec MHT 3D. Obydwa skanery mają dość krótki zasięg, 

Artec ma jednak mniejszy. Artec używa światła żarówki zamiast lasera jak Konica Minolta. 

Artec również wydaje się być lepszy w zastosowaniu do mniejszych obiektów, charakteryzuje 

się też lepszą dokładnością i rozdzielczością. Używając tych skanerów, programy które daje 

producent zostały użyte do pozyskania danych 3D. Jednakże, na rynku jest też dostępny 

program jak Geomagic, który może zostać użyty do post-processingu, do pracy na surowej 

chmurze punktów pozyskanej czy to z fotogrametrii czy też skaninngu. Polygon Editing Tool 

od Konici Minolty wydaje się nie działać najlepiej z nowym Windowsem 7 wersji 64-bitowej, 

jednak program od Artec jest w stanie wykorzystać komputer znacznie lepiej – można ustawić 

ilość rdzeniów procesora do obliczeń. 

Najlepszy model został osiągnięty przy użyciu skanera Artec MHT, który potrafi pozyskać 

dane z rozdzielczością do 0,5mm i dokładnością aż do 0,1mm. Jeżeli chodzi o końcowy 

model uzyskany w programie Artec, jest on dość dobry. Jednak, zdaniem autora, program 

Geomagic spisał się lepiej, gdzie jest więcej kontroli nad manipulacją modelu. Wygładzanie 

może tu zostać zastosowane z “uwzględnieniem krzywych”, gdzie model przy tych krzywych 

nie jest aż tak bardzo wygładzany i potrzebne linie – ostre krawędzie zostaną lepiej widoczne 

na modelu. 

Ostateczny model jest wyeksportowany w pliku 3D PDF a także w innych dodatkowych 

plikach, które można obejrzeć na komputerze. 

iii

Summary: 

Sculptures and other artifacts are exposed to damages and it is hard to avoid them. For 

cultural heritage preservation new replicas of these objects should be done. For this purpose 

the best solution is to use non-touching methods, like photogrammetry and three-dimensional 

scanning, which will not do any harm to the object. Then 3D digital model may be used and 

by applying of 3D printers the real copy may be done 

The purpose of the report was to investigate methods on making detailed digital models on 

example of a sculpture from Nidaros Cathedral. The goal was to get as accurate – detailed 

model as possible. There is comparison on photogrammetric, 3D scanning methods and 

available 3D modelling tools. 

To make a very detailed digital model of round, complex, and small objects – very big point 

cloud is needed. The point cloud has to be accurate with high resolution. To make such a 

point cloud from images any software needs a lot of time for computation. Also, computation 

of big amount of points in the data from scanning takes a lot of time. This is not because of 

low PC, but because of software limitations. Some scanners are able to make more dense 

point cloud with better accuracy than others. With higher resolution and better accuracy 

scanners become smaller, and also distance range is decreasing. Though, for small object 

smaller distance is required. Photogrammetry may produce also very good results, if only the 

material is non-reflective/shiny, or glass. 

In the project photogrammetric software has been used, such as PhotoModeler Scanner and 

Topcon ImageMaster, where both are able to create 3D surface from photographs, taken by 

non-metric camera. Both softwares provide camera calibration. The results at the end were 

quite good, but the sculpture is quite shiny and reflects the light, and this situation is not 

required for image matching and creating 3D points. Therefore, the model results with a lot of 

noise. Also, the time needed for DSM creating was very long and this part still needs some 

improvement. Free software from Autodesk – Project Photofly 2.0 was also tested. The 

application creates mesh and may be used by non-experienced users. Nevertheless, the results 

are not so accurate or the resolution is lower, it still may be used in most common situations. 

From laser scanning, Konica Minolta VI-910 was used for data acquisition, but also very 

interesting handheld small scanner from Artec was used. Both are created for small range 

distances; nevertheless Artec MHT seems to be better for smaller objects. It has better 

accuracy and higher resolution. In both cases, softwares recommended by the companies were 

used for modelling. Geomagic software was also used for post processing afterwards. Polygon 

Editing Tool from Konica Minolta seemed not working properly with new Windows 7 x64 

bits, but Artec was even able to use most of the processors cores for computations. 

The best model was achieved by applying small structured scanner from Artec with 0,5mm of 

resolution and accuracy up to 0,1mm. The model created using Artec software works good, 

but in the author‟s opinion Geomagic software works better, where smoothing may be done in 

the respect to curves. 

The final model is exported in 3D PDF file and other additional files 

iv

NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY 

DEPARTMENT OF CIVIL AND TRANSPORT ENGINEERING 

Report Title: 

Investigation on methods for making detailed digital models 

of sculptures and other artefacts 

Undersøkelse av metoder for å lage detaljerte digitale 

modeller av skulpturer og andre objekter 

Badanie metod dotyczących tworzenia szczegółowych 

modeli cyfrowych rzeźb i innych obiektów 

Name: 

Professor in charge/supervisor: 

Other external professional contacts/supervisors: 

Date: 25.07.2011 

Number of pages (incl. 

appendices): 90 

Master Project Work 

Thesis X 

Małgorzata Aulejtner 

Professor Knut Ragnar Holm 

Ph.D. Regina Tokarczyk 

Abstract: 

Digital modelling of real objects, like sculptures for cultural heritage preservation became a 

modern non-touching method. New methods are being developed. There are already existing 

methods like photogrammetry and relatively newer three-dimensional scanning. In this work 

comparison of these methods in connection with the software has been done. The main goal was 

to get detailed a model, which would represents the object as real one as best as possible. The 

model here is needed to make a real replica afterwards, by applying three-dimensional printer. 

The main limitation of the examinations was time period. Dada acquisition was not a problem, 

however the amount of data, and amount of generated point clouds itself was sometimes 

problematic. There were also some limitations of software – every computational step was taking 

too much time. Even though the used computer was very fast, the older software was not able to 

take full advantage of the hardware. It was also hard to set a proper time index to the quality of 

details. The best model was needed, the high resolution was required, what affects that time for 

processing increases. It was especially visible when it comes to the photogrammetric part, 

because the scanning method was more user-friendly. Geomagic software was also used for 

processing the point clouds. All results are compared, and the best model was made by using 

Artec MHT 3D Scanner in connection with Geomagic Qualify software. The scanner is capable 

to acquire data with 0,5mm resolution with 0,1mm accuracy. Photogrammetry methods may also 

give good results, though in this case, as the material of the sculpture was reflecting the light, it 

did not. The model resulted with big amount of noise. 

The final model is exported in 3D PDF file and other additional files. 

Keywords: 

1. Photogrammetry 

2. Camera Calibration 

3. Three-dimensional scanning 

4. Three-dimensional digital modelling 

5. Visualisation 

6. Comparison 

_________________________________________ 

(Signature)

iii

PREFACE AND ACKNOWLEDGMENTS 

This master thesis has been written for The Restoration Workshop of Nidaros Cathedral 

(Trondheim) request. I had opportunity to investigate various methods and instruments for 

three-dimensional modelling, where replica of a sculpture from the Cathedral was object for 

tests. I was able to work and test available instruments and software at the NTNU – The 

Norwegian University of Science and Technology in Trondheim, Norway. During the year as 

exchange student from AGH – The University of Science and Technology in Kraków, Poland, 

I had participated in a few measurement projects, which were based on digital 

photogrammetric and scanning methods. 

Thanks to Kristin Bjørlykke, working at The Restoration Workshop of Nidaros Cathedral, for 

borrowing the replica (sculpture of Archbishop) from the Cathedral to work on it. I got 

helpful information about the problems, which they had met before and historical background 

about the Archbishop itself. 

I am also very grateful to Odd Erik Mjørlund, manager in Geoplan 3D - company in Oslo, for 

giving introduction and opportunity to test Artec MHT 3D Scanner. 

I would like to express my gratitude to Ph.D. Regina Tokarczyk, working at AGH at the 

Department of Geoinformation, Photogrammetry and Remote Sensing of Environment for 

supervising the thesis in Poland, while I was studying abroad. 

Since the beginning of this thesis, there has been a continuous communication with Professor 

Knut Ragnar Holm, working at NTNU, at the Department of Civil and Transport Engineering, 

to whom I would like to express my grateful acknowledgments. I am thankful for contacts to 

people who were helpful to try more methods. 

v

SUMMARY 

Sculptures and other artifacts are exposed to damages and it is hard to avoid them. For 

cultural heritage preservation new replicas of these objects should be done. For this purpose 

the best solution is to use non-touching methods, like photogrammetry and three-dimensional 

scanning, which will not do any harm to the object. Then 3D digital model may be used and 

by applying of 3D printers the real copy may be done 

The purpose of the report was to investigate methods on making detailed digital models on 

example of a sculpture from Nidaros Cathedral. The goal was to get as accurate – detailed 

model as possible. There is comparison on photogrammetric, 3D scanning methods and 

available 3D modelling tools. 

To make a very detailed digital model of round, complex, and small objects – very big point 

cloud is needed. The point cloud has to be accurate with high resolution. To make such a 

point cloud from images any software needs a lot of time for computation. Also, computation 

of big amount of points in the data from scanning takes a lot of time. This is not because of 

low PC, but because of software limitations. Some scanners are able to make more dense 

point cloud with better accuracy than others. With higher resolution and better accuracy 

scanners become smaller, and also distance range is decreasing. Though, for small object 

smaller distance is required. Photogrammetry may produce also very good results, if only the 

material is non-reflective/shiny, or glass. 

In the project photogrammetric software has been used, such as PhotoModeler Scanner and 

Topcon ImageMaster, where both are able to create 3D surface from photographs, taken by 

non-metric camera. Both softwares provide camera calibration. The results at the end were 

quite good, but the sculpture is quite shiny and reflects the light, and this situation is not 

required for image matching and creating 3D points. Therefore, the model results with a lot of 

noise. Also, the time needed for DSM creating was very long and this part still needs some 

improvement. Free software from Autodesk – Project Photofly 2.0 was also tested. The 

application creates mesh and may be used by non-experienced users. Nevertheless, the results 

are not so accurate or the resolution is lower, it still may be used in most common situations. 

From laser scanning, Konica Minolta VI-910 was used for data acquisition, but also very 

interesting handheld small scanner from Artec was used. Both are created for small range 

distances; nevertheless Artec seems to be better for smaller objects. It has better accuracy and 

higher resolution. In both cases, softwares recommended by the companies were used for 

modelling. Geomagic software was also used for post processing afterwards. Polygon Editing 

Tool from Konica Minolta seemed not working properly with new Windows 7 x64 bits, but 

Artec was even able to use most of the processors cores for computations. 

The best model was achieved by applying small structured scanner from Artec with 0,5mm of 

resolution and accuracy up to 0,1mm. The model created using Artec software works good, 

but in the author‟s opinion Geomagic software works better, where smoothing may be done in 

the respect to curves. 

vi

TABLE OF CONTENTS 

1 INTRODUCTION .............................................................................................................. 1 

1.1 Project background ...................................................................................................... 1 

1.2 Cathedral and sculpture background information ....................................................... 1 

1.3 Three-dimensional printers .......................................................................................... 4 

1.4 Structure of the report .................................................................................................. 5 

2 THEORETICAL BACKGROUND .................................................................................... 6 

2.1 Review of similar projects ........................................................................................... 6 

2.2 Photogrammetry .......................................................................................................... 7 

2.2.1 Aerial Photogrammetry ........................................................................................ 7 

2.2.2 Close – range photogrammetry ............................................................................ 8 

2.2.3 Focusing ............................................................................................................... 9 

2.2.4 Image scale and accuracy .................................................................................. 10 

2.2.5 Coordinate systems ............................................................................................ 11 

2.2.6 Sensor principle .................................................................................................. 11 

2.2.7 Camera calibration - Interior orientation .......................................................... 11 

2.2.8 Exterior orientation ............................................................................................ 15 

2.2.9 Collinearity equations ........................................................................................ 16 

2.2.10 Direct Linear Transformation (DLT) ................................................................. 17 

2.2.11 Absolute orientation ........................................................................................... 17 

2.2.12 Bundle triangulation .......................................................................................... 17 

2.2.13 Matching types of digital images ....................................................................... 20 

2.3 Three-dimensional digitizers; Three-dimensional scanning ...................................... 21 

2.3.1 Time-of-light (TOF) measurements .................................................................... 22 

2.3.2 Phase-shifting measurement techniques ............................................................ 22 

2.3.3 Triangulation-based measurements ................................................................... 23 

2.4 Three-dimensional digital modelling and visualisation ............................................. 25 

2.4.1 Solid triangulated surfaces ................................................................................. 26 

2.4.2 CAD models ........................................................................................................ 27 

2.4.3 Visualisation ....................................................................................................... 27 

3 INSTRUMENTS AND SOFTWARE .............................................................................. 28 

3.1 Computer - workstation ............................................................................................. 28 

3.2 Photogrammetry ........................................................................................................ 28 

3.2.1 Camera: Canon EOS-1Ds (Body) ...................................................................... 28 

3.2.2 Lens: Canon 28mm f/2.8 .................................................................................... 29 

3.2.3 Topcon ImageMaster Software .......................................................................... 29 

3.2.4 PhotoModeler Scanner Software ....................................................................... 30 

3.2.5 Autodesk Project Photofly - Photo Scene Editor 2.0 Software .......................... 30 

3.3 Three-dimensional digitizing ..................................................................................... 31 

3.3.1 Konica Minolta VI-910 laser scanner ................................................................ 31 

3.3.2 Artec MHT three-dimensional scanner .............................................................. 32 

3.4 Geomagic Software; post-processing, modelling and visualisation .......................... 32 

4 EXPERIMENT ................................................................................................................. 34 


4.1.1 Image acquisition ............................................................................................... 34 

4.1.2 Topcon ImageMaster Software .......................................................................... 37 

4.1.3 PhotoModeler Scanner Software ....................................................................... 39 

4.1.4 Autodesk Project Photofly Photo Scene Editor 2.0 Software ............................. 42 

vii

4.2 Three-dimensional scanning ...................................................................................... 44 

4.2.1 Konica Minolta VI-910 laser scanner ................................................................ 44 

4.2.2 Artec MHT three-dimensional scanner .............................................................. 46 

4.3 Geomagic Software ................................................................................................... 47 

5 RESULTS, COMPARISSON AND ANALYSIS ............................................................ 49 


5.1.1 Camera calibration (PhotoModeler Scanner and Topcon ImageMaster) ......... 49 

5.1.2 Photogrammetric project concerning modelling of the sculpture (PhotoModeler 

Scanner and Topcon ImageMaster) .................................................................................. 51 

5.1.3 Autodesk Project Photofly Photo Scene Editor 2.0 Software ............................. 55 

5.2 Three-dimensional scanning ...................................................................................... 56 

5.3 Geomagic Software, modelling, post-processing software ....................................... 58 

6 DISCUSSION AND CONCLUSION ............................................................................... 61 

REFERENCES ......................................................................................................................... 67 

APPENDIXES ......................................................................................................................... 72 

viii

LIST OF FIGURES 

Figure 1.1 Nidaros Cathedral nowadays – west, front side ........................................................ 2 

Figure 1.2 Actual sculpture of Archbishop in Nidaros Cathedral .............................................. 4 

Figure 2.1 Photogrammetric principle of 3D measurement; example on convergent image 

configuration (Luhmann et al., 2006) ......................................................................................... 8 

Figure 2.2 Focusing and depth of field (Luhmann et al., 2006) ............................................... 10 

Figure 2.3 Perspective centre and principle distance (Luhmann et al., 2006) ......................... 12 

Figure 2.4 Effect of radial – symmetric distortion; example (Luhmann et al., 2006) .............. 13 

Figure 2.5 Effect of radial – asymmetric and tangential distortion; example (Luhmann et al., 

2006) ......................................................................................................................................... 14 

Figure 2.6 Effect of affinity and shear deviations; example (Luhmann et al., 2006)............... 14 

Figure 2.7 Interior orientation (Luhmann et al., 2006) ............................................................ 15 

Figure 2.8 Exterior orientation for terrestrial photogrammetry (Luhmann et al., 2006) .......... 16 

Figure 2.9 Methods and data flow for orientation and point determination (based on 

(Luhmann et al., 2006)) ............................................................................................................ 20 

Figure 2.10 Epipolar geometry ................................................................................................. 21 

Figure 2.11 Basic triangulation principle applied in scanning 

(http://www.impactstudiostv.com/Studios) .............................................................................. 23 

Figure 2.12 System setup with one bar pattern and one camera; example of structured-light 

scanning (http://www.rob.cs.tu-bs.de/en/research/projects/shape/) ......................................... 24 

Figure 3.1 Camera Canon EOS-1Ds (Canon, 2011) ................................................................ 28 

Figure 3.2 Lens Canon 28mm f/2.8 (Canon, 2011) ................................................................. 29 

Figure 3.3 Konica Minolta VI-910 laser scanner (Minolta and GmbH, 2011) ........................ 31 

Figure 3.4 Artec MHT scanner (Artec, 2011) .......................................................................... 32 

Figure 4.1 Photograph from image acquisition ........................................................................ 36 

Figure 4.2 Results from Topcon ImageMaster Camera Calibration ........................................ 37 

Figure 4.3 Textured mesh from one photo pair in Topcon ImageMaster ................................ 39 

Figure 4.4 Residuals on control points in camera calibration in PhotoModeler Scanner ........ 40 

Figure 4.5 Coloured point cloud of small part of the sculpture in PhotoModeler Scanner ..... 42 

Figure 4.6 Data flow using Autodesk Project Photofly software (Autodesk, 2011) ................ 43 

Figure 4.7 Final Maximum mesh in Autodesk Photo Scene Editor 2.0 Project Photo Fly ...... 44 

Figure 4.8 Merged point cloud in Polygon Editing Tool from Konica Minolta ...................... 45 

Figure 4.9 Merged and smoothed point cloud in Artec Scanner software ............................... 47 

Figure 4.10 Registration of point clouds in Geomagic; model of deviations .......................... 48 

Figure 5.1 Results of camera calibration from Topcon ImageMaster ...................................... 50 

Figure 5.2 Textured model from PhotoModeler Scanner; sculpture was sprayed with dust ... 54 

Figure 5.3 Shaded model from PhotoModeler Scanner, representing “hair”, 1mm resolution 54 

Figure 5.4 Textured model from Autodesk Project PhotoFly 2.0 ............................................ 55 

Figure 5.5 Model from Autodesk Project PhotoFly; converted and improved in Geomagic .. 56 

Figure 5.6 Model from Artec MHT scanner and Software ...................................................... 58 

Figure 5.7 Model from Artec MHT scanner, but data processed in Geomagic, which is 

perceived as the best one. ......................................................................................................... 60 

Figure 6.1 Final model from Geomagic, using Artec MHT data ............................................. 64 

Figure 6.2 Visual comparison of model – more detailed part of the sculpture – “hair”; top left 

Geomagic - “Artec”, top right Geomagic - “Autodesk”, bottom left Geomagic – “Konica 

Minolta”, bottom right “PhotoModeler Scanner” .................................................................... 65 

ix

Figure 6.3 Visual comparison of model – more sharp part of the sculpture – “collar”; top left 

Geomagic - “Konica Minolta”, top right Geomagic - “Autodesk”, bottom Geomagic – “Artec” 

.................................................................................................................................................. 66 

LIST OF TABLES 

Table 2.1 Simplified workflow for modelling: from point cloud to final model ..................... 26 

Table 3.1 Specification of Canon lens 28mm f/2.8 (Canon, 2011) .......................................... 29 

Table 5.1 Comparison on results of camera calibration using photogrammetric softwares .... 50 

Table 5.2 Comparison of photogrammetric software: ImageMaster, PhotModeler Scanner ... 53 

Table 5.3 Comparison on scanning systems: Artec, Konica Minolta, processing in Geomagic 

.................................................................................................................................................. 59 

Table 5.4 Comparison on results of alignment scans in Geomagic software .......................... 60 

LIST OF APPENDIXES 

A. 1 Specification of Canon Camera EOS-1Ds ....................................................................... 72 

A. 2 Report - results of camera calibration using PhotoModeler Scanner software ................ 76 

A. 3 Comparison on photogrammetric software used in the project including system 

requirements, import/export files, main features camera calibration and modelling 

manipulation tools .................................................................................................................... 78 

A. 4 Comparison of 3D digitizers: main features, specification: used methods, light, range, 

resolution, accuracy, etc. .......................................................................................................... 81 

A. 5 Comparison of software from scanning systems; main features, system requirements, 

model manipulation tools. ........................................................................................................ 83 

A. 6 Geomagic Qualify: main features, import/export files, system requirements and main 

manipulation tools used in the project ...................................................................................... 86 

x

1 INTRODUCTION 

1.1 Project background 

INTRODUCTION 

Sculptures are exposed to different damages, like atmospheric and so on. For many years, 

they have been getting to wear down and it is possible to see the signs of erosion. Something 

has to be done to preserve cultural heritage. Because of these problems many replicas are 

being done and they are replacing original forms inside the museums. Some of them are too 

fragile to use old methods and make plaster casts. There is a risk that touching the sculpture 

will destroy it completely. 

Nowadays, there are geodetic techniques which allow making three-dimensional digital 

models without touching the objects. It may be photogrammetric or laser scanning methods. 

The accuracy and resolution has been also improved over the time and it is possible to get 

0,2mm resolution with 0,05mm accuracy (Artec S scanner). This kind of model may be 

displayed on a screen and virtual museum may be created. Digital models can be also printed, 

using special three-dimensional printers which allow recreating the 3D shape of the object. 

These methods seem to be the best, because of no risk of destroying the original sculpture. 

Moreover, these printers are able to make a copy with good accuracy as well, usually with 

0,1mm layer thickness, where 3D dots size is around 0,05mm in diameter. 

The project is being done on The Restoration Workshop of Nidaros Cathedral request. They 

are trying to reconstruct all the sculptures and shapes of the Cathedral. Reconstruction process 

takes a long time and it is very tedious. Many characters have been reconstructed in plaster 

form or sculptures in stone. Around 4000 casts has been made, for preservation copy as a 

proof. In 1983 the Archbishop Palace was burnt. A lot of work and priceless documentation 

was lost in the flames. 

In November 2003, Vinn Design company from Oslo (Bache, 2003), have done some 

scanning in Nidaros. They made model of Prinsipp and Kong Sverre and made a real replica 

afterwards. The results were quite good, although some parts were not exact reflection of the 

real sculpture. Some small details were missing and sharp edges were being smoothed. The 

Cathedral needs more detailed and accurate models. As some of the sculptures are very small, 

or some details are very small, a proper method for acquiring the 3D data and modelling 

should be applied. To get better replica the higher resolution and more accurate model is 

needed. 

In the project investigation on methods of making detailed models has been done. Methods 

hereby mean existing photogrammetric software in use of non-metric commercial cameras 

and close range laser scanning. The software has been tested and the results are compared. 

The object of investigation is a sculpture – a head of Archbishop from the Cathedral, probably 

of Pål Bårdsson. It is a relatively small object, about 25x25x30 cm and there are a lot of small 

details and sharp edges, some small details are even smaller than 1mm. 

1.2 Cathedral and sculpture background information 

Nidaros Cathedal (Nidarosdomen/Nidaros Domkirke) is a church located in city centre in 

Trondheim. Figure 1.1 shows the front side of the Cathedral. It was established in 1152 and at 

that time it was Norwegian archdiocese until its abolition in 1537. After the reformation, it 

1

INTRODUCTION 

had been the cathedral of the Lutheran bishops of Trondheim (or Nidaros) in the Diocese of 

Nidaros. Romanesque and Gothic style are represented by architectural style of the cathedral. 

The style was also based on English cathedral in Canterbury. This is the largest chapel in all 

Scandinavian countries, where a king of Norway Olav II was buried. He interposed Christian 

religion in his country and for a very long time, his grave was a place of pilgrimages. Because 

of this phenomena, 40 years after his funeral the construction of the cathedral began. 

Nowadays, it is not possible to see the silver coffin of Olav, as it was moved to Denmark in 

1537 and remelted into coins. 

Building work on the cathedral started in 1070 and it was finished about 1300. Nevertheless, 

the cathedral had been damaged several times, mostly by fire, firstly in 1327 and again in 

1531. The nave west of the transept was destroyed and it was rebuilt long time after, in early 

1900s. Moreover, in 1708 it burned down completely except for the stone walls. After then, 

the cathedral had been through major rebuilding and restoration, which started in 1869, 

initially led by architect Heinrich Ernst Schirmes, and nearly completed by Christian Christie. 

In 2001 it was officially completed. However, maintenance of the cathedral is an on-going 

process. More information can be found on webpages: http://www.nidarosdomen.no/nb-NO/ 

(Nidaros) and http://snl.no/Nidarosdomen (Leksikon et al., 2009). 

Figure 1.1 Nidaros Cathedral nowadays – west, front side 

2

INTRODUCTION 

Generally, the sculptures in the cathedral represents roles in society or the Bible, like Jesus, 

Maria, kings, queens, etc. rather than portraits of real person. However, the sculpture used in 

the project (see Figure 1.2) is a medieval sculpture of Archbishop Pål Bårdsson. Gerhard 

Fisher, who wrote the jubilee book for the restoration of the cathedral (1965) presumes that it 

was Bårdsson, archbishop in the period 1333 – 1346. Fisher‟s guess is based on the 

assumption of building period a part of the church where the sculpture is located. This place is 

on the south side, in the Octagon – the oldest part of the cathedral. Having in mind that the 

building history is insecure when it comes to date, the portrait must be considered as a pure 

guess. Unfortunately, there is no information about who made the sculpture. The name of the 

artist is a relatively modern phenomenon. 

Pål Bårdsson died in 01.02.1346 in Nidaros cathedral, but the place of his birth is unknown. 

He was elected for archbishop in 1333. When it comes to his education, it is mentioned in the 

history that he was a cannon in Bergen from 1309. Later, he became magister in 1313. Pål 

represented also bishop in Bergen in law and diplomatic fields. Around 1320 he was mostly 

spending his time and do business abroad. He got also his PhD from the University in Oreland 

in both canonical and Rome law. What is more, he had a degree of a professor, which very 

few Norwegians had at that time. From 1327 he was also a chancellor of the king. It may be 

concluded that he was very wise and good man. More information can be found on webpages: 

http://www.katolsk.no/organisasjon/mn/erkebiskoper/15 (Organisasjon and Martinsen, 1996) 

and http://snl.no/.nbl_biografi/Pål_Bårdsson/utdypning (Leksikon and Dybdahl). 

3

INTRODUCTION 

Figure 1.2 Actual sculpture of Archbishop in Nidaros Cathedral 

1.3 Three-dimensional printers 

Since 2003 there has been a large growth in the sale of 3D printers, mostly because the cost of 

them has declined. The technology is being applicable in many different fields. Nowadays, 

there is large number of competing technologies and companies that produce such 3D 

printers. The main differences are in the way layers are built to create parts. Printers may use 

different tools for cutting the proper 3D surface, but also different materials. Some of them 

create bigger objects, whereas some are created for smaller and more detailed ones. 

Resolution, the most important issue in printing a sculpture with small details, is given in 

layer thickness, X-Y resolution in dpi. Usually layer thickness is around 0,1mm, while in X-Y 

resolution is comparable to that of laser printers. The particles (3D dots) are around 0,05mm 

to 0,1mm in diameter. 

4

1.4 Structure of the report 

INTRODUCTION 

In the beginning the report contains theoretical background about photogrammetry and 

scanning method. Information about camera calibration and computed features are given. 

Also, there is a description of some basic – principle equations which may be met in 

photogrammetry. When it comes to scanning, there is a briefing about laser scanning and 

structured – light scanners and the principle that they use – triangulation. 

Next section describes instruments used such as camera with lens, scanners and computer. 

There is also basic information about software: photogrammetric and used by canners for 

acquisition and also for post-processing. 

Later on, there are the results, which are divided into Photogrammetry and Scanning. There is 

also at the same time comparison of those methods. Some discussion may be found there as 

well. 

The last section is discussion and conclusions. It contains discussion on what the results 

showed and which method was the best for the project purpose. There are also figures 

comparing models from different methods, which are focused on more detailed areas of the 

sculpture. 

5

2 THEORETICAL BACKGROUND 

2.1 Review of similar projects 

THEORETICAL BACKGROUND 

Over the time, there were done similar projects concerning documentation of cultural 

heritage. Some of them were more precise and some were more generalized. For instance in 

paper 3D Color Imaging For Cultural Heritage Artefacts Hess and Robson (Hess and 

Robson, 2010) are showing how to use 3D laser scanners and close range photogrammetry for 

this purpose, they also made some comparison. In the paper An Optical Three-dimensional 

Measuring Techniques for a Detailed Non-contact Data Acquisition…Floth and Breuer (Floth 

and Breuer, 2010) are showing mostly laser scanning techniques for data acquisition and 

process chain. However, in the What is the Future of Metric Heritage Documentation and Its 

Skills? (Blake, 2010) Blake is focused on future software that could be used for cultural 

heritage preservation. He describes new methods and shows that online web – based software 

may be future. 

In some projects, referring to paper works, the same software has been used. For example 

speaking of ImageMaster – photogrammetry software, was used by (Wojtas, 2010) in Offthes-helf 

Close-range Photogrammetry Software for Cultural Heritage Documentation at 

Stonehenge. She also used PhotoModeler Scanner for this purpose and she also made camera 

calibration. Nevertheless, it must be mentioned, that she used PI-3000 which is previous 

version of Topcon ImageMaster. She tested this software on Stonehenge rock. Also, (Kochi et 

al.) in PC-based 3D Image Measuring Station With Digital Camera…, used PI – 3000 

software. Their case of study was historical ruins of Parthenon but also Hdriaphooroi – 

statues. What is more, (Chmielewski and Szulwic) in Niemetryczne zdjęcia cyfrowe w 

fotogrametrii bliskiego zasięgu w systemie Topcon PI-2000, Chmielewski and Szulwic also 

used the same software, however their test object was architectural building, but Kazanaa 

(Kazanaa, 2010) , used the software on the old fountains abbey stone (English heritage). 

These methods were applied for non-metric commercial cameras and make process automatic 

and easy to use. For the modelling of the telamon in the archaeological museum ImageMaster 

was also applied in connection to laser scanning data – using TOF ZScan system of Menic 

Software - (Brutto and Spera, 2011). In the same combination as in the project ImageMaster 

and the same scanner Konica Minolta is used by Barnett (Barnett et al.) while Recording 

Prehistoric Rock Art. PiCalib software for camera calibration from Topcon was also used in 

Master Theses supervised by Ph.D. Regina Tokarczyk at University of Science and 

Technology (AGH, Kraków) (Pawlak and Pulchny, 2009), but also in (Jędrzejek and Łącka). 

Some experiments with PhotoModeler Scanner have made Alyilmaza with others (Alyilmaza 

et al., 2010) during Measurement of Petroglyphs (Rock of Arts…), where the objects of 

interest were drawings on the rock like Qobustan petroglyphs. From laser scanning, 

mentioned before, Konica Minolta was also used for a purpose by Barba (Barba et al., 2011). 

They used this scanner with Tele lens for documentation of artefact from the Roman period, 

found in Spanish city Merida. For modelling, visualisation and texture they used Geomagic 

and Photoshop. 

Geomagic, software that is able to handle point clouds from laser scanning and make models 

was applied by (Akca et al.) in Recording and modeling of cultural heritage objects with 

coded structured light projection systems and other similar papers, done by the same persons, 

where objects: Weary Herakles, the Khmer Head, Herakles Farnese - sculptures , Lady 

6


praying painting were used for documentation. They mentioned that they had used optoTOP- 

HE and optoTOP-SE, Breuckmann GmbH, systems for 3D digitalization, acquisition, and 

recording. Moreover, they compared two similar applications: Geomagic and Polyworks, 

which both seems to be good. Though, (Tucci et al., 2011) in Effective 3D Digitization of 

Archeological Artifacts… also used Geomagic for documentation of small heritage objects. 

They used triangulated based laser scanner NextEngine‟s 3D Scanner HD, which is generally 

used for surveying small and medium objects. Bigger artifacts were scanned by Z-Scan by 

Menci Software photogrammetric system. Texture was captured simultaneously. 

For small objects handheld laser scanner seems to be very convenient and easy to use. 

Bonfanti with others (Bonfanti et al., 2010) used such a scanner – HandyScan 3D model HZ, 

which is triangulated based LiDAR system. For modelling and visualisation RiscanPro and 

3D Reshaper were applied in their project. 

There is much more photogrammetric software available on the market, or laser scanners, 

which use triangulated based system for small objects surveying. Clorama software from 

3Dixpplorer is one of the photogrammetric software which is able to reconstruct 3D shapes 

from pictures. Pictran or iWitness may be used in example for camera calibration, but they are 

not able to create a mesh. 

There are also some open source softwares, available even via internet, which are able to 

create 3D models from pictures. It is believed these types of software are the future. They are 

low cost and they do not require very specific photographs. The user does not have to know 

photogrammetric principles and all the calculations are made in one step. The results of 

course are worse than using other software and there is very little info about the accuracy. 

However, in many cases this might be enough. Deseilligny and Clery (Deseilligny and Clery, 

2011) tested one of these software – Apero and Micmac. Also, Balestrinia and Guerra 

(Balestrinia and Guerra, 2011) used Arc3D for 3D reconstruction. On the market there are 

also visible Autodesk Project PhotoFly and Photosynth which are also open source licensed 

and produce point cloud or mesh, or both 

2.2 Photogrammetry 

Photogrammetry is the science of making measurements from photographs. By using 

photographs it is possible to determine geometric properties of objects by specific 

measurements and computations. It is possible to create three dimensional models as well. 

By proper calculation, camera station for each photograph may be described. From 

intersection of light rays from each photo position of 3D point may be obtained. For this 

purpose usually bundle adjustment with least-squares optimization is applied. 

Photogrammetry can be dated to the mid-nineteenth century and words may be explained as: 

Photo – light 

Gram – drawing 

Metry – measurement 

2.2.1 Aerial Photogrammetry 

The camera is mounted in an aircraft and is usually pointed vertically towards the ground. 

Multiple overlapping photos of the ground are taken as aircraft flies along a flight plan. These 

7


photos are processed in a stereo mode – nowadays usually with 3D glasses connected to the 

workstation – to see two photos at once in stereo view. These photos are usually used for 

making Digital Elevation Model (DEM) and orthophotomaps. 

2.2.2 Close – range photogrammetry 

The camera is located close to the object, handheld or on a tripod. Usually this type of 

photogrammetry work is non – topographic. It is used usually to model buildings, engineering 

structures, vehicles, cultural heritage objects, etc. 

To be able to describe an object in 3 dimensions there is a need to be at least two pictures of 

the object taken in a proper way. At the beginning of photogrammetry pictures were analogue 

and specific instruments were used to match pictures and use them for map making for 

instance. Nowadays everything is computerized and there are plenty of cheap, commercial 

digital cameras which may be used for this purpose. There are also available metric cameras, 

very accurate, with certificates of calibration, made for geodetic measurements. Their 

specification is that they have fixed settings like: principle distance, aperture, etc. 

Knowing camera parameters and location of the cameras, which is computed during camera 

orientation (interior, exterior, relative and absolute orientation – or in one block during bundle 

adjustment), which is mainly to coordinate photos in the space, it is possible to compute 3D 

point from triangle – rays intersection (using at least two photos). Figure 2.1 shows this 

principle. As these parameters are known, rays may be recreated. After the identification of 

common points on each image it is possible to gain the position of this point in 3D space, 

which is the intersection of the recreated rays. 

Figure 2.1 Photogrammetric principle of 3D measurement; example on convergent image 

configuration (Luhmann et al., 2006) 

Firstly, the object of interest should be examined, if it is big/small and, what kind of features 

it contains, etc. In respect to shape of the object, the proper camera with lens (wider angle or 

not) should be chosen. If applying lens with wider angle the image scale may be bigger and 

more details may be captured. But, it may also lead to bigger error (distortion etc.) and more 

photographs needed to cover the entire object. 

8


For computation of orientation, control points should be measured. In some cases they should 

be marked, for better accuracy or to measure them with Total Station to get Global 

coordinates. An another situation, marking is not needed at all, because natural features 

(natural points, lighter or darker spots for instance) may be used for orientation – then the 

computations are in local coordinate system. 

No matter what types of control point are used, these have to be measured. Some softwares 

are able to mark points in the image and reference the same points between the images 

automatically (if special coded points used), some are able to measure semi-automatically and 

in others all measurements have to be done by the user. Usually, if automation is available the 

software has option for sub-pixel measurements by applying computer vision methods. Every 

software has requirements, when it comes to amount of points which are necessary for 

computation. It depends on applied algorithms and calculation methods. Unfortunately it is 

hard to say what exact type the specific software uses, the companies do not want to share this 

information. Nevertheless, the main principle is that computations are based on bundle 

adjustment and least-square normalisation. 

Next, the software computes all the necessary parameters to get information about orientation 

and link the photos between them. The same moment there is accuracy assessment, and at this 

moment the user should have a look on the results, if they are sufficient. Sometimes the 

corresponding points may be wrongly referenced or measured at a wrong place. This 

assessment helps to find those errors. It is also possible to remove lens errors from photograph 

and transform them from central to orthogonal projection. 

From that point, point cloud – 3D may be generated. In the past, it was done manually, but 

todays methods give an opportunity to generate 3D points automatically, using advanced 

computer vision. Image matching with sub-pixel accuracy give good prospects. 

Unfortunately, in some cases there might occur miss-match and points have to be checked by 

the user. For generation of Digital Surface Model (DSM) the area on the image should be 

specified. It helps software to limit time for image-matching, while not all the photograph 

contains the object of interest. From that point, cleaning the data is being started. Modelling 

and visualisation tools are described further in the report. 

2.2.3 Focusing 

For accurate measurements, the object of interest has to be sharp. Then, the object has to be in 

a depth of field area, where the object will be sharp. The object is sharp when the diameter of 

the circle of confusion u’ does not exceed a diameter of ca. 1pix for digital sensors. Hence, 

not only the object point P focused in distance a is sharply defined, but all points between P1 

and P2 appear sharp. Figure 2.2 illustrates this situation. Depth of field is dependent on f – 

number (aperture), distance to the object and focal length. What is more, the depth of field 

increases by stopping down, enlarging distance to object and reducing focal length. 

9

Where: 

T – depth of field 

R – the furthest sharply distance 

S – the nearest sharply distance 

u’ - circle of confusion 


Figure 2.2 Focusing and depth of field (Luhmann et al., 2006) 

2.2.4 Image scale and accuracy 

Scale of the image m is connected with distance to the object, principle distance and sensor 

size (image format). 

Where: 

h – object distance 

c – principle distance 

X – distance in object space 

x’- distance in image space 

In order to achieve sufficient accuracy and delectability of fine detail at the scene, the image 

scale M has to be defined appropriately with respect to the available imaging system and the 

exterior environmental conditions. 

10 

(2.1) 

Accuracy is connected to the image scale, because if the bigger scale, the more details are 

visible in the photo. What is more, configuration of the image may have influence on the 

accuracy, especially when it comes to Z direction. It is connected with height-to-base ratio 

(h/b) and if the cameras were situated parallel or convergent to each other. Also, generation of 

3D point cloud – resolution is dependent on image scale

2.2.5 Coordinate systems 


From image to model is a long way. Just after recording, photo is in image coordinate system 

(defined by camera); while in the end the model is in global coordinate system, or at least in 

object local system. Several coordinate systems may be specified: 

� Image coordinate system 

It is two dimensional image-based reference system of rectangular Cartesian coordinates x’, 

y’. Usually the origin of the image of frame coordinates is located at the image centre. In 

digital images, origin is located in left upper corner and values of pixels are specified by rows 

and columns, and thus mainly the coordinate system has to be transformed to the centre of 

projection on the image 

� Camera coordinate system 

It is similar to the image coordinate system, it is only moved by z’ axis – principle distance c 

– the origin on this system is the spatial position of the perspective centre 

� Object coordinate system 

It is also known as world coordinate system, or global, Cartesian XYZ coordinate system. The 

system is used for all the photographs and object. It is defined by reference points on the 

object, if the points are measured in global coordinate system, or if not - it may be defined as 

local coordinate system of the object, where all the photographs are referenced to the one 

(chosen by the used). 

� 3D instrument coordinate system 

Coordinate system is oriented by one of used 3D measuring machine. This is not directly 

related to any superior system or particular object. 

2.2.6 Sensor principle 

“Sensors consist of a large number of light-sensitive detector element, that are arranged on 

semi-conductor modules either line-wise or matrix-wise (line or matrix sensor). Each detector 

element (sensor element) generates an electric charge that is proportional to the amount of 

incident illumination falling on it. The sensor is arranged such that the charge at each 

individual element can be read out, processed and digitized.” (Luhmann et al., 2006) 

There are sensors based in CCD (Charge Coupled Device) or CMOS technology – they differ 

on used material and transportation of the electro-magnetic information. CMOS sensors 

(complementary metal oxide semi-conductor) seem to be better in many ways. They have less 

power consumption, lower manufacturing costs, high image frequencies, high dynamic range 

and low image noise. 

2.2.7 Camera calibration - Interior orientation 

Camera calibration is a process to get specification of the camera, parameters of interior 

orientation. Some cameras have a certificate, where camera calibration has been done in the 

lab. But, commercial cameras do not have it in the beginning. In these cameras there is a 

possibility to change lens, aperture, focal length, which changes camera features. 

In addition to make accurate 3D measurements – good (accurate) camera calibration is 

needed. At this moment there are softwares on the market which provide calibration for 

commercial cameras. Some of them may be used for processing at the same time. 

11


To make camera calibration, pictures of special calibration chart should be taken with fixed 

settings: fixed focal length, focus, principle distance, aperture; and it is more secure to at least 

fix the lens with a tape to prevent eventual moving. They should be taken also on the same 

day with the same conditions, e.g. temperature and humidity. The test field may differ. Most 

of software companies developed their own calibration pattern; however it is usually possible 

to create a new one. Using pattern that the company recommends to use – calibration 

computation is automatic, otherwise mainly all the points have to be measured manually or at 

least semi-automatically. Every software has his own recommendations how to take pictures 

(from which angles etc.) and how many. It is also possible to make self – calibration on the 

field, but the results may not be as accurate as using test field. Without camera calibration a 

slightly different equations are used and it is very hard to find the error when it occurs. 

No matter what kind of software is used the same features, listed below are computed. The 

algorithms may be slightly different but the principle is the same – to get the most accurate 

results – with Least Square Method (LSM). 

Perspective centre and distortion 

Mathematically, the perspective centre is defined by the point of central perspective that is the 

point through which all straight lines from all image rays pass. Perspective centre depends on 

chosen aperture. This point may be defined both external and internal of objective. In the ideal 

case these points are equal. Similarly in ideal case, principle distance c is equal to the image 

distance a’, still there is always some error. What is more, lens distortions, which will always 

occur, also change interior geometry. Geometric basics of perspective centre and distance 

shows Figure 2.2.The shift of the point on the image may be computed: 

Where: 

τ – angle of incidence 

τ’- exit angle 

r’ – image radius of an image point 

∆r‟- radial shift due to distortion 

Figure 2.3 Perspective centre and principle distance (Luhmann et al., 2006) 

12 

(2.2)


Computed features of camera calibration; interior orientation are: 

� Principle Point (image coordinates) 

Nadir of the perspective centre with image coordinates (x’0, y’0= for standard cameras 

approximately equal to the centre of the image) 

� Principle distance 

It is normal distance to the perspective centre from the image plane; approximately equal to 

the focal length of the lens when focused at infinity: c≈f’ 

� Parameters of functions describing imaging errors, distortions, etc. (∆r’): 

o Radial distortion 

It is the major imaging error, the most effective, in most camera systems. It is connected to 

the lens and its error. It is related with refraction at each individual component lens within the 

objective. It may also change while changing focusing distance and the object distance. Figure 

2.4 illustrates the effect of radial imaging error. 

Distortion curve is usually modelled with a polynomial series with parameters K1 to Kn 

((Luhmann et al., 2006) - based on Brown, 1971): 

Figure 2.4 Effect of radial – symmetric distortion; example (Luhmann et al., 2006) 

13 

(2.3) 

Parameter K2 is often correlated with K1. Parameter K3 can normally be determined to 

significant value only in special cases, f.e. for fish eye lens. 

o Tangential (asymmetric or decentric) distortion 

Radial – asymmetric distortion, called tangential or decentric. It is mainly caused by decentric 

and misalignment of individual lens elements within the objective 

Figure 2.5 illustrates the effect of decentric distortion. 

By following function this distortion may be compensated ((Luhmann et al., 2006) - based on 

Brown 1971): 

( ) 

( ) 

(2.4)


Figure 2.5 Effect of radial – asymmetric and tangential distortion; example (Luhmann et al., 

2006) 

o Affinity and shear of the image coordinate system 

These components represent error in due to orthogonallity and scale image coordinate system 

to coordinate axes. 

Figure 2.6 represents an example of the effect of this error. 

The following function can be used to provide an appropriate correction: 

Figure 2.6 Effect of affinity and shear deviations; example (Luhmann et al., 2006) 

Parameters of tangential asymmetric, distortion B1, B2, and affinity and shear C1, C2 often 

exhibit high correlation with other values of interior orientation. 

o In some cases, there are some other additional parameters describing imaging 

error, however they have less influence and are rather very small. 

14 

(2.5)


Total correction 

The individual terms used to model the imaging errors of most typical photogrammetric 

imaging systems can be summarised as follows: 

Interior orientation 

Knowing these parameters, the (error-free) imaging vector x’ can be defined with respect to 

the perspective centre (hence, the principle point). 

Figure 2.7 illustrates geometric principle of interior orientation. 

[ 

] [ 

Where: 

x’p, y’p – measured coordinates of image point P’ 

x’0, y’0 – coordinates of the principle point H’ 

∆x’, ∆y’ – axis – related correction values for imaging errors 

2.2.8 Exterior orientation 

Figure 2.7 Interior orientation (Luhmann et al., 2006) 

This step is to orient camera in the space, it consists six parameters which describe this 

position in camera coordinate system. As the project is in close range photogrammetry, not 

aerial, only the example on close range situation is shown. 

Six parameters are: three coordinates X0, Y0, Z0 of the principle point in image coordinate 

system and three rotation angles α, κ, ω– around three axes x, y, z; what is shown in Figure 

2.8. 

15 

] 

(2.6) 

(2.7)


Figure 2.8 Exterior orientation for terrestrial photogrammetry (Luhmann et al., 2006) 

Matrix R of rotation for exterior orientation is a set of combination of sinus and cosinus 

functions of rotation angles mentioned before. Matrix X0 describes position of the camera. 

2.2.9 Collinearity equations 

These equations are the core in the photogrammetry. From these equations it is possible to get 

object coordinates from image coordinates (exterior orientation). These equations are also 

base for other computations, like Bundle Adjustment or Direct Linear Transformation. 

Collinearity equations: 

( ) ( ) ( ) 

( ) ( ) ( ) 

( ) ( ) ( ) 

( ) ( ) ( ) 

Where: 

x’, y’, z’ – image coordinates of corresponding points (measured on the picture) 

z’ – is usually equal principle distance z’=-c 

x’0, y’0 – coordinates of the principle point H’ in image coordinate system 

∆x’, ∆y’ – correction terms of the image coordinates 

X, Y, Z – object coordinates of corresponding points (measured on the picture) 

X0, Y0, Z0 – object coordinates of principle point H 

These equations describe the transformation of object coordinates (X, Y, Z) into corresponding 

image coordinates (x’, y’) as functions of the interior parameters and exterior orientation 

parameters of one image. 

An alternative form may be given, if the object coordinate system is transformed by shift to 

the perspective centre and orientation parallel to the image coordinate system. 

These equations demonstrate clearly that each object point is projected into a unique image 

point, if it is not occluded by other object points. The formulas effectively describe image 

generation inside a camera by the geometry of a central projection. 

16 

(2.8)


The collinearity equations are fundamental equations of analytical photogrammetry. They are 

suitable for direct use of observations, also in an over-determined least-squares adjustment. 

They are used to set up the equation system for spatial intersection, space resection and 

bundle triangulation. 

2.2.10 Direct Linear Transformation (DLT) 

These equations let determine the orientation of an image without need for approximate initial 

values. It is based on collinearity equations, extended by an affine transformation of the image 

coordinates. There is also no need for fixed coordinate system in the camera. 

DLT equations: 

Where: 

x, y – measured comparator or image coordinates 

X, Y, Z – 3D coordinates of the reference point 

L1 – L11 – coefficient, DLT parameters – from these the parameters interior and exterior 

orientation may be derived 

DLT needs minimum 6 points measured on the picture; but for better result, eventual error 

detection and accuracy assessment there is need to measure more than 6. What is more, using 

DLT equations is not easy to detect errors in reference points. 

2.2.11 Absolute orientation 

This orientation describes how the images are situated in the space in global coordinate 

system. It means the local coordinate system may be rotated, scaled and moved due to 

reference points. It is used mostly in aerial photogrammetry. Sometimes in terrestrial, though 

for small objects like sculpture it is not needed, because only the local coordinate system is 

used. 

2.2.12 Bundle triangulation 

17 

(2.9) 

Bundle block adjustment, multi–image triangulation, multi–image orientation is a method for 

the simultaneous numerical fit of unlimited number of spatially distributed images (bundles of 

rays). By use of tie points, single images are merged into a global model which the object 

surface can be reconstructed in three dimensions. The most important constraint is that all 

corresponding (humongous) images rays should intersect in the corresponding object point 

with minimum inconsistency (Least Square method). In an over – determined system of 

equations, an adjustment technique estimates 3D object coordinates, image orientation 

parameters and any additional model parameter, together with related statistical information 

about accuracy and reliability. It is one set of simultaneous calculations, triangulation is the 

most powerful and accurate method of image orientation and point determination in 

photogrammetry.


The bundle adjustment has a lot of advantages, because it may be applied with irregularly 

arranged and often unfavourable image configurations. It is more complex structure of normal 

system of equations. There is complex generation of approximate values for the unknowns 

and arbitrary oriented object coordinate systems. It is possible to combine adjustment of 

survey observations and conditions, where also several imaging systems can be calibrated 

simultaneously. 

Adjustment model - Gauss-Markov linear model - based on collinearity equations 

This principle is based on that the unknown parameters are estimated with maximum 

probability. 

Condition for the residuals results (L2 - normalization): 

∑ [ ] 

Mathematical model of the bundle block adjustment is based on the collinearity equations, 

which are mentioned before in equation (2.8) above. 

18 

(2.10) 

The structure of these equations allows the direct formulation of primary observed values 

(image coordinates) as functions of all unknowns‟ parameters in the photogrammetric 

imaging process. The collinearity equations, linearized at approximate values, can therefore 

be used directly as observation equations for least-square adjustment according to the Gauss- 

Markov model. 

It is principle of the image coordinates of homologous points which are used as observations. 

The following unknowns are iteratively determined as functions of these observations. 

� 3D object coordinates for each new point i (up, 3 unknowns each) 

� exterior orientation of each image (uI, 6 unknowns) 

� Interior orientation of each camera k (uc, 0 or ≥ 3 unknowns each) 

The bundle adjustment therefore represents an extended form of the space resection: 

Where: 

i – point index 

j – image index 

k – camera index 

( 

( 

Standard form, the linearized model (functional model): 

With n observations and u unknowns, n>u. 

⏟̂ 

⏟ 

⏟ 

̂⏟ 

) 

) 

(2.11) 

(2.12)

Where: 

Solving the normal equations: 

Variance – covariance matrix: 


̂⏟ 

⏟ 

⏟ 

⏟ 

⏟ 

⏟ 

( ⏟ 

19 

⏟ 

⏟ 

⏟ 

⏟ ) 

⏟ 

⏟ 

⏟ 

⏟ 

(2.13) 

(2.14) 

(2.15) 

The adjustment is solved iteratively. In this case the corrected approximate values in iteration 

k are used as new starting values for the linearized functional model of next iteration k+1, 

until the sum of added corrections for the unknowns is less than a given threshold. 

Precision and accuracy 

Standard deviation a posteriori, the empirical standard deviation of unit weight is given by: 

With redundancy: 

̂ √ 

Standard deviation of a single unknown xj is given by: 

̂ ̂ √ 

Where qjj are the elements of the principle diagonal of matrix Q 

(2.16) 

(2.17) 

RMS – root mean square. In many cases adjustment results are reported as RMS instead of 

above defined standard deviation. The RMS value is the square root of the mean squared 

difference between n given nominal values Xnom and corresponding adjusted observations Xobs 

√ ∑( ) 

(2.18)


RMSE – root mean square error – RMS error of adjusted observations with respect to mean 

of adjusted observations 

√ ∑( ̅) 

20 

(2.19) 

To orient two images or more, tie points have to be defined. These points may be natural 

points which are visible on both pictures. However, they may be marked before. These points 

may be defined in a specific shape – coded points, where every software may have different 

pattern. In some cases the points (or at least few of them) should have known coordinates 

(XYZ), for orientation to global coordinate system, but for close range and in the project it is 

not necessary. Points should be arranged around the object and/or could be on the object. 

Picture should cover as best (as biggest area as possible) the object with marked points around 

it. Referenced points should not be located in a common plane, this situation may give errors. 

Depending on methods (algorithm, transformation etc.), or step in orientation different 

amount of control points is needed. In Figure 2.9 is specification of point determination on 

each field. 

Figure 2.9 Methods and data flow for orientation and point determination (based on 

(Luhmann et al., 2006)) 

2.2.13 Matching types of digital images 

Matching is a process in computer vision that matches pictures to each other. These are 

methods which are used to identify and uniquely match identical objects features. 

Feature-based matching 

This is usually the first step and it is mainly identifying as many corresponding features as 

possible in all images. Specifying area of interest or any other information can be used to limit 

the search space and minimalize mismatches. This matching is done by extracting distinct


features from images, and then identifies those features that correspond to each other by 

comparing features attributes and location. Types of features may be: edge elements, line 

segments, curve segments, circles, ellipses, regions, where cost function may be used. 

Correspondence analysis based on epipolar geometry – see Figure 2.10. In the figure the 

situation is simplified, it depicts two cameras looking at point X. Virtual image plane is placed 

in front of the focal point of each camera to produce unrotated image. OL and OR represent the 

focal points of the two cameras. Points xL and xR are the projections of point X onto the image 

plane. When the projection of point xL is known, then the epipolar line eR-xR is known and the 

point X projects into the right image, on a point xR, which lie on this particular epipolar line. 

When the points xL and xR are known, their projection lines are also known. If the two image 

points correspond to the same 3D point X the projection lines must intersect precisely at X. 

Furthermore, the epipolar lines are parallels to the line OL-OR between the focal points. 

Figure 2.10 Epipolar geometry 

Area-based multi-image matching 

It is more precise and accurate matching than the one mention above. Correlation and least - 

squares method are used in this method. In addition, geometric information, epipolar 

geometry can be used to improve accuracy and reliability. This type of matching compares 

the grayscale values of patches of two or more images, trying to find features based on 

similarity in those grayscale value patterns. 

Object-based matching, Symbolic 

This matching use as well geometric but also radiometric object model, where the 

corresponding image regions are determined iteratively. The algorithm uses cost function and 

description of symbols. In this matching, the relation between sample and correct choice 

stimulus is established arbitrarily by the experimenter. 

2.3 Three-dimensional digitizers; Three-dimensional scanning 

Three-dimensional digitizer is a device that analyses a real world objects or environment to 

collect data on its shape and if possible e.g. colour. The collected data are usually 3D point 

clouds which can be used to construct digital, three dimensional models. This may be used for 

several purposes, like industrial design, reverse engineering, etc. and of course documentation 

of cultural artifacts. Every scanner (or set of scanners inside one company) has its own 

software for data acquisition and processing. The software for processing, when the point 

clouds are captured, has been also developed separately by different companies. 

21


In the beginning the purpose of the model, or the object, or both has to be investigated and in 

respect to this, proper scanner should be used. In some cases it is needed to put additional 

targets, for registration of scans, which are taken from different positions. Some companies 

required their own coded targets. Some scanners do not need any special targets on the object 

for referencing the scans. Aligning is done by approximate specification of corresponding 

features which are easy to define and algorithms compute needed parameters, by applying 

high precision matching computations. 

Some scanners are also available to capture a texture – to record photos, and put the real 

colour on the 3D points. Model has real appearance afterwards. During the data acquisition, 

everything depends on used scanner. Usually, for the close-range the object should be visible 

and separated from background if possible. If the background is far enough, it is not recorded, 

because of range limitations of the scanner. For scanning it is also important, that the object is 

not made from reflective material/ shiny/ or glass. Some scanners may cope with these 

materials. Mostly, when the scanner uses laser or light projection, the light may be reflected 

(or go through the object – glass) and then the model may result in noise, badly described 3D 

position of the points. 

After data acquisition it is time for selection of the data. At this stage, the background and all 

the necessary surfaces should be removed. These cosmetics help software with later alignment 

and consequence with better results. Next, registration of the point clouds should be done. As 

mentioned before, for this purpose corresponding points should be measured/ specified on the 

scans. Here, again, software specifies how many points are necessary. Later, the fine 

registration is being computed, very accurate computations, where all the scans are being 

align simultaneously. Next, the scans may be merged into one regular point cloud. After this 

modelling / edition of the 3D surface may be done and this is described further. 

2.3.1 Time-of-light (TOF) measurements 

This type of measurements is preferred at longer ranges. A pulse TOF detects the time a laser 

beam is reflected back to the receiver detector. The accuracy depends on how precisely we 

can measure the travel distance of the light; which is 3,3 picoseconds is the time taken for 

light to travel 1mm. In these scanners we may say that accuracy is relatively constant for the 

whole volume of measurement, but increasing the distance the accuracy will be decreasing. 

Also, with increasing distance dense resolution of the point cloud is decreasing. These types 

of scanners are able to gain about 5000 - 10000 points per second. Distance range is from 

200m +. Of course, these numbers are approximate – every laser scanner – every company 

may have different specifics. These types of scanners are also used in aerial scanning – 

LiDAR (Laser Detection and Ranging). 

2.3.2 Phase-shifting measurement techniques 

Time-of-light method may also be realized by amplitude modulation, using phase difference. 

This technique is usually more precise than normal TOF; but there is a higher possibility to 

get big – gross error. It is because the distance is computed by the difference in a phase of 

sent beam and reflected. It is easy to find the difference but it may be not obvious to get the 

amount how many times the phase was repeated. These types of scanners are able to gain 

even 100000 points per second. Distance range is from up to 80m and accuracy about 1-2mm. 

Of course, these numbers are approximate – every laser scanner – every company may have 

different specifics. 

22

2.3.3 Triangulation-based measurements 


Laser scanners may be based on different principles and use slightly different techniques, 

motors, mirrors, laser beams, structured-light patterns and so on. The triangulation principle is 

very old; it was demonstrated by Greeks for navigation and by astronomers more than 2000 

years ago. 

The sensors recording the data, images, at first, of course, were analogue, but during the time 

they were improving and now, information is transformed into digital form. 

When previous methods may be used for long distances this one may be used only for short 

range. Triangles are basis for many measurements techniques, in laser scanning that principle 

was developed in the early 80‟s. The triangle is as follows: laser source, which project a beam 

of light on an object; camera – sensor, which collect the position of a beam; and object of 

interest. Figure 2.11 explains triangulation principle. Knowing position and angles between 

laser source and camera it is easy to compute 3D point on the object. This method is much 

more precise than the others. This type is mostly used for acquiring high resolution and 

detailed data when it comes to small objects. For cultural heritage and preservation these 

scanners are common to use. Laser scanning is good non-contact way to produce 3D complex 

models of sculptures and other object for documentation. This method may be used for other 

purpose as well. Distance range, quality and time rate may differ very much in these scanners. 

There are many different types upon this principle and a lot of companies make such 

scanners. 

Material which may be scanned with current technology include clay, was, rubber, plastic, 

bone, wood, ferrous metal, nonferrous metal, glass, stone, and ceramics, but not every type is 

capable to scan those surfaces. 

Figure 2.11 Basic triangulation principle applied in scanning 

(http://www.impactstudiostv.com/Studios) 

23


Single point scanners 

The scanner uses only one single ray beam projection and Camera sensor receives only one 

point at the time. The point is acquired on the intersection ray beam with an object that the ray 

meets. The Imaging lens may differ, for example there may be only one lens; or one lens with 

dual aperture mask( inserted next to the diaphragm of the lens creates two spots on CCD 

detector and a unique peak-position/ separation relationship); or two lenses on both sides of 

the project. These additional components give better accuracy. 

Slit scanners 

The principle is quite similar to single point scanners, though the projector generates laser 

plane instead of only one ray. This method gives more information at the time where whole 

profile may be received from one scan. The main inconvenience of these scanners is the 

compromise between the field of view and depth resolution. The other disadvantage is their 

relatively poor immunity to ambient light. Some improvements have been done and indoor 

acquisition is relatively good, but outdoors there might occur some problems. 

Pattern projection scanners; structured-light 

The projector generates a light pattern (no laser): moiré patterns, circular or line profiles 

(horizontal or vertical). “The most popular method use binary coded orphases shift fringe 

patterns. Grey-code binary images use multiple frames with increased resolution to encode a 

pixel on the CCD with its corresponding range. Subpixel resolution is obtained by detecting 

the edge transitions in the highest resolution image. Other methods use sinusoidal phase 

encoding the measure range.” (Blais, 2004) In practise, the more frames are used the better 

accuracy. These scanners are popular as well, because of low-cost projectors and full 3D 

volume can be acquired quickly in just few video frames. Disadvantage in comparison to strip 

scanners is smaller depth of view. Also, there might occur defocus (when the e.g. image is out 

of focus) “of the projected pattern due to fact that a larger projector lens is needed to collect 

as much light as possible from the light course.“ (Blais, 2004). Figure 2.12 below illustrates 

Pattern projection principle. 

Figure 2.12 System setup with one bar pattern and one camera; example of structured-light 

scanning (http://www.rob.cs.tu-bs.de/en/research/projects/shape/) 

24


Hand-held scanners 

There are also scanners available on the market which are small, hand–held. They are usually 

used for very small objects and the most interesting thing is that they do not need marking any 

control points. Scanning is done by capturing frames and each frame is oriented (referenced) 

to the previous automatically (if the scanner is not moving too fast). Here for instance, in 

comparison to the scanners, one scan means several frames referenced to each other, every 

frame is a point cloud and set of this frames creates one big point cloud. 

2.4 Three-dimensional digital modelling and visualisation 

In computer graphics three-dimensional, digital modelling is the process of developing a 

mathematical representation of any surface or object via specialized software. The model may 

be represented in many different ways: 2D image, animation, short walk-through video and so 

on. 

In the project a 3D model is derived from point cloud (from scanning or photogrammetry) and 

how to get this point cloud is described before. In modelling from these 3D points there is a 

need to filter the point cloud. All data are weighted with some kind of error and there is 

always some kind of noise that is unwelcome in modelling. Therefore, these bad defined 

points should be removed, smoothed, or by special filters the position of points may be 

changed by applying a specific method. Also, at the beginning the data contain a lot of points 

and they might be reduced as well, to improve work (it is meaningful especially in time 

needed for processing). 

Some objects are very complicated and it is very hard to cover the entire object with points. 

There, the software encloses a tool – “Filling holes”, where all these holes may be filled. The 

method may differ in every software. 

All these filters may be used on points; they might be used on triangulated mesh as well. It is 

easier to work and reduce noise and data before, using points. To get a surface from points, 

triangulation / wrapping / meshing tool should be employed. It is possible to use only points, 

but if some curves may be specified, they might be used as break lines. Not every software 

gives this opportunity and mostly is allows making Triangulated Irregular Network (TIN) or a 

skeleton (defined by lines, arcs, etc.). On created mesh it is usually possible to use similar 

filters as on points, what was mentioned before. 

Very important part for mesh is that the reparation tool should be run. It checks topology, 

errors of the surface, like if there are any intersections, etc. 

When the model of the surface is ready, model of the light and reflection may be created. It is 

more visual side. At this point, light and type source may be chosen. The user may set a 

position of a light, but also a material of the model and how much is it reflecting the light. 

It is also possible to put texture on the model. It may be default, only one colour, or from 

photographs. If photos are referenced to the model it is very easy to put the real texture on the 

model. It gives the model more realistic outlook. 

The last part is to make files, or hard copies to show the final model. It may be 2D image 

from one of the view, but it may be also 3D file. There is a set of different 3D files that may 

be exporter and viewed, one of them is 3D PDF, GIF or VRML. 3D PDF gives quite a lot of 

25


opportunities, because the model may be rotated, but also, the light source and material may 

be changed as well, and the file may be open in Adobe Reader. Other opportunity is creation 

of video file, key frames may be chosen by the user, and short video may be exported. 

Simplified workflow, with listed operations, in modelling and visualising from 3D point cloud 

to final product is shown in Table 2.1. 

Table 2.1 Simplified workflow for modelling: from point cloud to final model 

One regular 3D point cloud 

Filtering of point cloud Removing noise, occluded point 

Smoothing algorithms 

Some manual edition if needed 

Filling holes (if exists) 

Reducing number of points 

Triangulation Generation of TIN, 3D surface 

Filtering of TIN (if needed) Filling holes (if exists) 

Smoothing algorithms 

Removing spikes 

Reparation of surface (topology, intersections, etc.) 

Reducing number of triangles 

Model of light and reflection (visualisation) 

Light source 

Type of light 

Place of light 

Illumination 

Reflection 

Texture mapping Real texture from photographs 

Or unreal texture 

Some additional visual, display settings Depending on the software 

Export output 2D images 

3D files, for example: 

3D PDF, VRML, etc. 

Video files 

2.4.1 Solid triangulated surfaces 

Collection of 3D points, which create vertices that are connected with each other and creates 

triangles (TIN). This type usually defines the volume of the object they represent, like a rock 

etc. From this collection 3D models may be created usually in software using proper 

algorithms. This method is mainly used in connection to data derived from 3D scanning or 

photogrammetry, where point clouds can be gained. This method is used for shapes, forms, 

where exact shape of the object is hard to define, like rectangles, shapes which are easy to 

define may help to improve the model. Curves easy to define may be used as break lines and 

have impact on created surface. 

26

2.4.2 CAD models 


These models may be also at first derived from 3D points, but the principle of this model is 

that the skeleton of the object creates model. Surface is represented as the boundary of the 

object, not its volume. These are easier to work than solid models. Shape of the object may be 

defined by straight lines, circles, ellipses etc. This method may be employed when the shape/ 

boundary is easy to define, e.g. buildings. 

2.4.3 Visualisation 

After obtaining a 3D model, next step is to visualize the model. Every model may be 

displayed differently. The purpose of the model specifies the final look. 

� Texturing 

To gain a photo-realistic model, the texture from photographs should be used. These photos 

may be from scanning (if scanner acquires colour photographs) or from photogrammetry. 

There may be used different texture as well, which will depend on the operator who will 

choose the proper settings. 

� Rendering 

It is usually the last step. It is what the final scene will look like. It includes where the camera 

will be placed, where to put the light source and what kind of light – this will affect shadows, 

reflections, transparency and other special effects, like adding e.g. background features (grass 

etc.) 

The very last part is representation of the model – exporting of final method files like 2D 

images, animation, etc. 

27

3 INSTRUMENTS AND SOFTWARE 

3.1 Computer - workstation 

INSTRUMENTS AND SOFTWARE 

Computer used for the project purpose was very good and fast. The main specifications are: 

� Microsoft Windows 7, Service Pack 1, based on x64-bits system type, 

� Processor: Intel Xeon CPU X5650 2,67 GHZ, 2661 MHz, 6 cores, 

� 24 GB RAM physical memory, 

� Graphic card, display: NVIDIA Quadro FX 4800, 1,50 GB RAM, resolution: 

1920x1080 

� 1,82 TB hard disc drive 

From the description it is possible to see, that the PC features are good enough for used 

methods in the project. It is at least enough for running the software that the companies 

require to have. 


3.2.1 Camera: Canon EOS-1Ds (Body) 

The camera used in the project is professional digital SLR camera. CMOS 11 megapixels full 

35mm frame sensor with 8,4µm x 8,4µm pitch size. The camera covers almost every other 

type of photography from landscape to portrait; photo journalism etc. The base of camera 

contains the large battery pack and allows for the integration of a vertical hand grip and 

control system. EOS-1Ds sensor because of full frame, there is no crop in the field of view 

(without focal length multiplier). The sensor has slightly larger pixel pitch, than others 

cameras, because of its larger effective imaging area. This, in theory will lead to more 

sensitivity, dynamic range and lower noise. More specification may be found in Appendix A. 

1 and visual appearance of the camera in Figure 3.1. 

Figure 3.1 Camera Canon EOS-1Ds (Canon, 2011) 

28

3.2.2 Lens: Canon 28mm f/2.8 


The used lens is light in weight and quite small. Minimum Focus Distance is close – 305mm. 

Lens has a 5-blade aperture. Angle of horizontal view is 65 degrees and vertical view is 46 

degrees. Specification may be found in Table 3.1 and visual appearance of the lens in Figure 

3.2. Also, more information about the Canon camera and lens can be found on the webpage 

http://www.canon.com/ (Canon, 2011) 

Table 3.1 Specification of Canon lens 28mm f/2.8 (Canon, 2011) 

3.2.3 Topcon ImageMaster Software 

Figure 3.2 Lens Canon 28mm f/2.8 (Canon, 2011) 

The software is built on the PI-3000 photogrammetry software. The version used in the 

project was 2.0 and it trial version, available only for 30-days. The software allows accurate 

3D models from stereo photographic image taken with a standard digital camera. 

ImageMaster is able to create automated 3D surface models, Ortho Images and xyz point 

clouds – the latter at a fraction of the cost of laser scanner. It allows measurements, TIN, 

contour lines or cross section creation; calculations of the models, drawing plotting or 3D 

model display and editing and so on. Using coded targets or at least circular it is possible to 

measure their centre automatically with sub-pixel accuracy. Similar, the software is also 

available to recognize corners. The company also provides camera calibration – ImageMaster 

Camera Calibration Software with their own calibration chart. More information about the 

Software and other instruments that the company offer can be found on webpages: 

http://www.topcon-positioning.eu/ (Topcon, 2011), http://imagemaster3d.com/ (Topcon, 

2008), http://www.terrageomatics.com/ (TerraDat et al.), and 

http://www.topconpositioning.com/ (Topcon, 2009) 

29

3.2.4 PhotoModeler Scanner Software 


The software provides the tools to create accurate, high quality 3D models and measurements 

from photographs. This process is called photo-based 3D scanning. Results are similar as 

from laser scanner. This scanning produces a dense point cloud from photographs of textured 

surfaces. The software includes also meshing, filtering and clean up tools. Matching may be 

done by using coded targets, or not coded or without any targets – then the SmartMatch 

function may be used by the software. It is also possible to measure circular target with subpixel 

precision, based on advanced computer vision techniques. This software provides also 

camera calibration with its own calibration chart. More information about the software can be 

found on the webpage: http://www.photomodeler.com/ (PhotoModeler, 2011) 

3.2.5 Autodesk Project Photofly - Photo Scene Editor 2.0 Software 

Autodesk‟s software, which is available for free to download from the Autodesk‟s website. It 

is open source software available for everyone. It allows anyone with a digital camera to 

create 3D models from photographs thanks to advanced computer vision technologies 

developed by Autodesk. Project Photofly automatically converts photographs into “Photo 

Scenes”, which includes photorealistic 3D model. Uploaded Images to a server are being 

processed and ready Photo Scene file is sent back once the computation is over. While 

waiting for computations there is no need to have open window – it is possible to ask for an email 

when it will be finished. When the Images are stitched properly, a draft mesh is 

computed automatically always as a result. However, we may refine the mesh, change quality 

for Mobile, Standard and Maximum: 

� Mobile – fast, medium resolution mesh, suitable for viewing on mobile devices; 

� Standard – high resolution textured mesh, best for visualization on the desktop, or 

� Maximum – very high density mesh, suitable for manipulating in external 

applications. 

The software also provides simple cleaning the 3D mesh, defining referenced points and 

distances or defining coordinate system. It is also possible to make some measurements on a 

model, create lines and polylines. 

The software allows creating an animation and a movie and exporting to e.g. YouTube. 

Photo Scene Editor is very easy to use and anyone may use, because of free availability. 

There is also no need to have a very specific camera; it is commercial software for everyone. 

The Project Photofly 2.0 technology preview will expire on December 31,2012. More 

information about the software, and the software may be downloaded from the webpage: 

http://labs.autodesk.com/utilities/photo_scene_editor/ (Autodesk, 2011) 

Appendix A. 3 represents software comparison on many different fields and introduces to 

main features and used tools in the project. 

30

3.3 Three-dimensional digitizing 

3.3.1 Konica Minolta VI-910 laser scanner 


The laser scanner is based on triangulation, slit beam principle. Figure 3.3 represents this 

scanner. The laser beam is scanned using a high – precision galvanometric rotating mirror, 

and 640x480 individual points can be measured per scan. The VI910 is provided with three 

interchangeable lenses that can accommodate measurement objects of various sizes and 

distances from the lens. The scanner incorporates the same automatic focus technology used 

in modern cameras. The CDD and RGB filter acquire rich, 24-bit full-colour images. Using 

these pictures it is able to get true-colour models. Complete fine scan (unsurpassed speed) 

takes 2,5 seconds and measures 307 200 points. 3D digitizer may be used without a host 

computer and recorded data are being saved onto Compact Flash memory card. Scanners 

integral LCD viewfinder can be used to set camera parameters and as view-finder to frame the 

shot or review the data. Thanks to these features it may be used wherever the subject is 

located. With dynamic range magnification mode very contrast objects are not a problem 

anymore. Fine mode gives precision of +- 0,008mm and accuracy of +- 0,10mm can be 

achieved on the Z – axis; X +-0,22mm and Y +- 0,16mm (with Fine mode and using Tele 

lens). The scanner is able to measure at distance 0,6 – 2,5m. However optimal 3D 

measurement range is 0,6-1,2m. 

Konica Minolta uses Editing Polygon Tool software (PET) for data acquisition and 

processing. It controls scanner and it allows easily polygonize, edit, and convert the scanned 

data into any of several common formats. Multiple scans can be easily registered and merged 

into single model. Editing functions are available like: fill holes, filter irregular polygons and 

noise, and perform smoothing. 

More information about the scanner system and software may be found on the webpage: 

http://www.konicaminolta.eu/ (Minolta and GmbH, 2011) 

Figure 3.3 Konica Minolta VI-910 laser scanner (Minolta and GmbH, 2011) 

31


3.3.2 Artec MHT three-dimensional scanner 

The scanner is based on light pattern projection, triangulation principle. This bulb flashes light 

pattern is projected onto the object and the camera record this pattern. Figure 3.4 represents 

MTH scanner. It is possible to get up to 15 frames per second, so moving around the object 

may be quite quickly with still good result. The scanner has also ability to capture the texture. 

3D resolution is 0,5mm with 3D point accuracy up to 0,1mm and 3D accuracy over distance 

up to 0,15% over 100cm. Working distance for this scanner is 0,4-1m and data acquisition 

speed up to 500000 points per second. 

Artec Scanner software is used for data acquisition and processing. It is possible to align 

scans and register into one coordinate system. After than Fusion all scans together is needed 

and optimizing the grid with fill holes and smooth tools may be applied. It is also possible to 

texture the model from photos taken by the scanner. 

Figure 3.4 Artec MHT scanner (Artec, 2011) 

Appendix A. 4 represents comparison of 3D digitizers and contains more details on their 

specification. There is also mentioned Artec S scanner, because this instrument has the best 

accuracy from all Artec scanners. There was a plan to test this one as well, but finally it was 

not able to borrow this one. Appendix A. 5 illustrates comparison on software that mentioned 

scanner use for data acquisition and processing. 

More interesting information can be found on webpages: http://www.artec3d.com/ (Artec, 

2011) and http://www.exact3dscanner.com/ (Metrology) 

3.4 Geomagic Software; post-processing, modelling and visualisation 

Geomagic is a leading provider of 3D software for creating digital models of physical objects. 

The company got numerous awards for technologies and owns six patents. There are three 

editions: Studio, Qualify and Wrap.: 

� Geomagic Studio is mainly used in reverse engineering, product design, rapid 

prototyping and analysis. It is created for transforming 3D scan data and polygon 

meshed into accurate, surfaced 3D digital models. 

32


� Geomagic Qualify is made for accurate, graphical comparisons between digital 

referenced models, and as-built parts for first-article inspection, production inspection 

and supplier quality management. Qualify is powerful report designer, and also the 

first inspection software that allows creating fully interactive 3D documents that can 

be viewed by Adobe Reader. 

� Geomagic Wrap enables the transformation of point cloud data to 3D polygon meshes 

for use in manufacturing, design and analysis. 

Mostly all of them are able to do/make the same things, there are just some differences that 

one is able to do something more than another and vice versa. 

Geomagic Qualify was used in the project for processing point clouds. It was tested in 

aligning and registration of point clouds into one coordinate system, removing noise, filters 

and mesh creation, also with some smoothing filters. 

Geomagic supports all 3D digitizers, cameras and scanners in XYZ/ASCII formats and 

handles ordered and unordered surface and volume data. 

Appendix A. 6 shows all main features of Geomagic Qualify, system requirements, main 

features and manipulation tools used in the project. 

More about the software capabilities may be also found on the webpage: 

http://www.geomagic.com/ (Geomagic, 2011) 

33

4 EXPERIMENT 


4.1.1 Image acquisition 

EXPERIMENT 

Image acquisition was taken few times, for tests. The sculpture is made of quite shiny material 

and therefore to get better results different settings were used. However, some of the settings 

were fixed for every acquisition. 

Fixed settings: 

� ISO = 100 

ISO system is in other words sensitivity to light of the sensor, also Film speed. Lower speed 

index requires more exposure to light to produce the same image density as a more sensitive 

film. In photography, the reduction of exposure corresponding to use of higher sensitivities 

generally leads to reduced image quality (like higher image noise, etc.) The higher film speed, 

the more grain on the image will occur. 

To achieve the best image quality the lowest film speed was used in the project. 

� Aperture = 22 

It is a hole or opening through which light travels. More specifically, the aperture is the 

opening that determines the cone angle of a bundle of rays that come to a focus in the image 

plane. The aperture determines how collimated and admitted rays are, which is of great 

importance at the image plane. If an aperture is narrow, then highly collimated rays are 

admitted, resulting in a sharp focus at the image plane. If an aperture is wide, then sharp focus 

is only for rays with a certain focal length. It also means, that sharp image will be around 

what the lens is focusing on, the rest will be blurred. Focusing principle was also described 

before in section 2.2.3. Moreover, the aperture determines how many of the incoming rays are 

actually admitted and this how much light reaches the image plane (the narrower the aperture 

-> the darker the image for a given exposure time). 

In order to get as sharp image as possible, the aperture was the narrower as possible. This 

setting changes highly lens distortion parameters and thus it have to be unchanged during the 

acquisition. 

� Focusing = ca. 0,5m 

The distance where the object is will be focused; the image will be sharp at this distance from 

the camera to the object. This distance was set in a way, to get sharp object – the sculpture 

and cover most of the image with the object. This setting also changes highly lens distortion 

parameters and it was fixed for the whole image recording 

� Format picture = 4064x2704pixels, 

This is the maximum resolution that is possible to choose, for the type of used camera. It 

depends on used sensor. 

� Image quality: JPG(the highest quality) + RAW (TIFF) 

The camera gives an opportunity to acquire in JPG, but also in RAW file. RAW file gives 

more opportunities with processing the image. It contains more information and uses no 

34

EXPERIMENT 

compression. RAW file contains minimally processed data from the image sensor and they 

have to be processed, or convert to print or edit them. Disadvantage is physical size of the 

image, which is a few times bigger than JPG. 

These were the most important settings, which stayed fixed and the same camera calibration 

was used for every picture. This was relevant especially for availability of comparison the 

results. 

Other camera settings which were slightly changing during the acquisition 

� Exposure time 

Shutter speed,, it is the effective length of time a camera‟s shutter is open. The total exposure 

is proportional to this exposure time, or duration of light reaching the image sensor. 

This setting was changing, because of different lighting conditions. The image acquisition 

was always inside the building and rather in dark places and this time was from ca. 1.5sec. to 

2.5sec. It is also connected with chosen ISO speed and aperture. Lower speed ISO and the 

narrower aperture needs more time for exposure in order to get better quality image, not too 

dark. 

� Light 

Acquisition took place in the building, always with lights. Firstly only lights in the room were 

used. Second – round light source – ring flash, that was fixed on the lens. Third – additional, 

separate two moving lights were implemented, in that case sheets were used to cover this light 

a bit due to too strong/ direct light 

� Additional 

Dust spray was used in addition to cover the sculpture and remove reflection – used only 

during one image recording, because the visual appearance was not very slightly for later 

texturing, etc. 

� White balance 

White balance is the global adjustment of the intensities of the colours (primary colours: R- 

red, G – green, B – blue). An important goal of this adjustment is to render these colours, as 

neutral colours, naturally. In camera it is possible to choose one of the auto programme; 

custom mode, or specify a number. The number here describes the colour temperature of the 

light in Kelvin. 

The setting was changed when light conditions were changed and custom mode was chosen 

from the menu. Camera is able to define white balance from a taken picture of white object 

(the camera is able to define the temperature from this photo), and this kind of picture was 

taken. 

� Background 

In general the background was white wall. In the beginning the background was usually the 

floor with the rest of the room, and the position of camera was changed. To improve results, 

the background was changed. The sculpture lay down on the pile of books and stood on the 

table. Because the additional lights which stood on the tripod were used, changing position of 

them was difficult. Only one wall was available. For complete image recording only the 

object of interest was moved – rotated. Also the camera always stood on the tripod in the 

same place – only height was changed. 

35

EXPERIMENT 

� Tripod 

For image recording tripod for the camera was always used, to reduce blur of applied long 

exposure time. Shutter time was also set for 0,5sec, to avoid camera movements and then blur 

while touching the camera. 

The best pictures were taken, with additional lights and without flash and these were chosen 

for processing. In PhotoModeler Scanner a few photos with dust were used as well, to 

compare the results. Figure 4.1 illustrates one of the photographs taken during image 

acquisition. It is possible to see that the photo is quite good; but it was not possible to avoid 

reflectiveness of shiny material and some pixels are “lost” (too bright, sometimes too dark). 

Additional control point around and on the sculpture were used for better bundle adjustment 

results. There was also scale bar to be able to scale the project. After all, a lot of images have 

been recorded and some of them may be found in folder: Canon\Photos including photographs 

for camera calibration. 

Figure 4.1 Photograph from image acquisition 

36

4.1.2 Topcon ImageMaster Software 

EXPERIMENT 

Camera calibration 

For camera calibration in Topcon the test field from the software was used. It was hanging on 

the wall, because of software requirements. Then five photographs were taken from every side 

(right, left, up, down and front). Afterwards camera parameters were computed automatically. 

Marking and referencing points is automatic. Figure 4.2 is a snapshot from calibration of the 

camera, which was used. 

The most important things which need to be remembered during the acquisition are: - first line 

of points should be as near as possible to the edge of the picture - and the chart should cover 

as much as possible the whole picture size. Also, very important for photogrammetry is to set 

focus length, principle distance and aperture and fix it for acquisition, because these 

parameters change the parameters of the calibration. 

New camera calibration was saved in a new project file in folder Topcon ImageMaster\Project 

files\Camera Calibration Canon 28mm 

Figure 4.2 Results from Topcon ImageMaster Camera Calibration 

Photogrammetry project 

During the work and processing the software was easy to use. The circular targets were easy 

to mark with subpixel accuracy – available in the software. Every point had to be clicked. The 

software was also able to measure corners with subpixel accuracy, but it was not used in the 

project. Next, the bundle block adjustment and all the computations worked fine. The 

software is able to use DLT equations instead of bundle adjustment, e.g. for an unknown 

camera. To coordinate system and scale, distances between three control points were used. 

These were measured with a scale bar. Afterwards, using stereo pairs the area for DSM 

creation was chosen. It is enough to draw the polygon on at least one photo pair. Photo pairs 

may be displayed in stereo view, when special polarizing glasses and 3D monitor are 

available. The polygon is being drawn simultaneously on the other photo pairs. To create 

DSM it is possible to choose only one photo pair or all of them and one mesh will be created. 

37

EXPERIMENT 

In the project both ways have been tested. After all, the best combination was to create DSM 

using separate pairs. The software may use cross-correlation or least-Square Matching as 

matching method. Computations take some time, and it needs more time for high resolution 

mesh. Also, exporting takes some time. Software does not give so many tools for mesh 

editing and improving. Some results have been exported and imported in Geomagic, It did not 

get any better results and no more investigations were done. 

Steps taken while using the software: 

� Import appropriate photos to the project. In the experiment 12 photos were used. 

� Orientation, bundle block adjustment. For different arrangement of photos, different 

amount of point is required. For this purpose at least 7 corresponding points was 

defined on every picture. If the coded or not coded circular points were used it is 

possible to find them automatically with subpixel accuracy. For computation, photopairs 

have to be defined by the user. The software use bundle adjustment but for some 

reasons it needs photo-pairs. Next stage is just to run the process and computations are 

being done automatically. 

� After that, photo-pairs may be displayed in stereo-view. Pictures are being calculated 

to remove distortion, change central projection to orthogonal to make possible 

displaying stereoscopic view, so it also respects orientation of the images. 

� Later on, it is recommended to specify area at least on one stereo pair for TIN 

creation– triangulated 3D point cloud. 

� Next, running TIN creation – there are some settings that may be changed. It is 

possible to create mesh only from one pair or use all of the pairs. It is also possible to 

create mesh with checked some filters (mean/ median) as well. Median filtering was 

mainly used in the project. For texturing only one photograph may be used, but also all 

of them, though one of them should be defined as basic one. When separate photopairs 

were used for TIN creation, one of them was set as basic. 

� The results may be displayed as 3D point cloud, shaded triangles or textured from 

pictures. Figure 4.3 illustrates view of the software with one textured mesh – using 

only one photo-pair. 

� Final model has not been reached. There were met some problems with TIN creation 

and merging the separate TINs. Exporting process was not the best solution, and 

therefore, Geomagic was not used for any improvement. The main reason of stopping 

the research with that software was because a lot of noise was produced affecting with 

wrong surface, mainly because of mismatching in shining areas. The project file may 

be found in folder Topcon ImageMaster\Project files\ArchBishop 

38

EXPERIMENT 

Figure 4.3 Textured mesh from one photo pair in Topcon ImageMaster 

4.1.3 PhotoModeler Scanner Software 

Camera calibration 

For this calibration the software require 12 photos, from each side (left, right, up and down) 

and with rotation of a camera with +90º and -90º. In that case it is easier to put test field on 

the ground or on the table – depending on used focus, lens and object of interest. In the 

project the table was used. Test field for calibration was also used the one that software 

require. 3D frame was also applied, however it was hard to take good pictures and the 

software compute parameters without sufficient accuracy and therefore this method was 

skipped. Similarly to Topcon‟s software, the chart should cover as much as possible the whole 

picture size and the first line on points should be as near as possible to the edge of the picture. 

Afterwards the calibration was computed automatically. Marking and referencing points is 

automatic. New camera was saved in project file in folder PhotoModeler\Project files\Camera 

calibration. Figure 4.4 below is snapshot from the camera calibration project. In the picture 

residuals on each point is shown. 

39

EXPERIMENT 

Figure 4.4 Residuals on control points in camera calibration in PhotoModeler Scanner 

Photogrammetry project: 

To process the photographs there is a need to reference control points between photographs, 

to be able to compute orientation parameters. Because circulars points were used around the 

object, point marking could be automatic. At least six points between the pictures have to be 

referenced manually. Then project may be processed – initial process. After then automatic 

reference could be executed and all of the points can be used. This is a very helpful tool and 

may improve results, because of using more points (this usually results with better 

adjustment). Also, when some points have not been marked for some reasons, they can be 

also marked with subpixel accuracy – when circular (only by defining rectangular area of 

point location on the photo). It is possible to process only few photographs in the project and 

after that all of them. In the project though, every stipe of photographs were computed 

separately. After that, all photos were oriented together. For some reasons, the computations 

failed when all the photographs were taken into the account for the first “processing”. 

For DSM creation software may use option - “use the best photo pairs”, where residuals, 

height to base ratio and angle between photographs are being taken into consideration. 

Maximum project residual quality – the lower the better accuracy; Base to Height Ratio 

should be from 0,1 to 0,5; and angle should be less than 30º (photos should not be too 

convergent) – these are as recommendations from the software. Tool for selection of the best 

photo-pairs is very helpful, because photo-pairs do not have to be specified from the 

beginning like in Topcon‟s software, but the best photo-pairs may be chosen automatically. 

Then, using selected pairs and additional settings like resolution, the point cloud is being 

generated. Then, if the results are fine, point clouds may be processed – it means: reduce the 

noise and triangulate the surface. DSM creation with mesh processing also takes some time, 

especially when high resolution is needed. The results may be exported, what was done in the 

project, and afterwards the files have been imported in Geomagic. However, the software was 

not able to make big improvement, probably because of small amount of points, and the 

surface was already created. There was no more investigation considering improvement in 

Geomagic, because the test did not give significant conclusion. 

40

EXPERIMENT 

In the project there were 12 photos used – 6 pairs with few more pair, that the software 

founded good for DSM creation. Also, in comparison to the Topcon‟s software, all the 

available control points were used, because this software has an ability to mark and reference 

them automatically. Project files may be found in folder PhotoModeler\Project files 


� Import appropriate photos to the project. 

� Orientation, bundle block adjustment. For this purpose at least six corresponding 

points were measured at every picture. If the coded or not coded circular points are 

used it is possible to find them automatically with subpixel accuracy. It is also possible 

to reference the points automatically, however only when the pictures are already 

“initial” oriented. Next stage is just running process and computations are being done. 

� After that, the project was idealized – it means that used pictures are being 

transformed to ideal form. Idealizing tool uses calibrated camera parameters and the 

lens distortion is being removed from the images. Also, it re-maps (pixel by pixel) 

image by non-centred principal point and any non-square pixels. After then the project 

was to be reprocessed - recomputed, what is recommended in order to get better – 

more accurate results. 

� Later on, it is recommended to specify area at least on one picture to create DSM – 3D 

point cloud. 

� Next, running DSM creation – there are some settings that may be changed. It is also 

possible to create mesh in the same time using some filters as well, however mesh and 

filters may be used afterwards. Setting, that may be changed for DSM creations are: 

o Sampling rate – 3D points are spaced approximately this distance apart on the 

surface; higher number results in more points; higher resolution 

o Distance from the main created surface – below or above it 

o Sub-pixel matching – recommend, for more accurate surface 

o Super-sampling factor, factor that also increase accuracy, but also time for 

computation, factor that is used for subpixel method 

o Matching region radius – radius that the algorithm is looking for pixels, to 

make matching between photo-pairs. Larger is slower with smoother results, 

but maybe useful if the texture features are large. Smaller is faster but may be 

noisier. Lower number reduces time but may produce more noise 

o Texture type – number that specifies if the matching algorithm should respect 

texture more or less, the lower number means that source images have a weak 

random non-repeating texture, where the biggest number indicates that images 

have a regular repeating texture. Also lower number produces a denser result, 

but sometimes with more noise. 

� The software uses stereo pairs for point cloud generation – it means “the best photo 

pairs” was chosen. 

� Based on points, TIN is being created, smoothing, fill holes filters may be used there 

as well. Every tool for point cloud modification has been used in the project with 

default settings, such as merging, noise reduction, smoothing and filling holes. 

� The results may be displayed as points, shaded triangles or textured from pictures. 

Figure 4.5 below represents snapshot from the software with mesh (mesh illustrates 

small area of the sculpture – “hair”). It is visible there are a lot of holes, even though 

photographs were taken around and cover that area, but there should be miss-match, 

because of different colour and reflection recorded on the images taken from different 

angle. 

41

EXPERIMENT 

Figure 4.5 Coloured point cloud of small part of the sculpture in PhotoModeler Scanner 

4.1.4 Autodesk Project Photofly Photo Scene Editor 2.0 Software 

The software is open source - available for free to download from Autodesk website. The 

software is able to create mesh from a set of the photographs. Interface and use of the 

software is very user friendly. There is no need to know basics of photogrammetry. These 

features make the software able to be used by everyone. 

Figure 4.6 is showing data flow in during the process. If in the sent photo scene, there are 

some bad stitched photographs, they may be stitched manually, by measuring at least four 

corresponding points on three photographs. In the project 154 photographs were used. In 

every photo at least 4 corresponding points were measured, for better alignment. 

Photogrammetric process is being done by sending the photos with point to the server and 

ready photo scene is being sent to the user when it is finished. Unfortunately is hard to say 

what is the accuracy and resolution of the mesh. The mesh was also exported and imported in 

Geomagic. In the Autodesk‟s software it is possible to see some errors in the surface, and 

therefore the model was improved in Geomagic. Nevertheless, the video file was exported as 

well from Autodesk‟s software and they may be found with project files in folder 

Autodesk 

42

EXPERIMENT 

Figure 4.6 Data flow using Autodesk Project Photofly software (Autodesk, 2011) 


� Creating a new Photo Scene by selecting appropriate photos 

� Next the photos are being uploaded to the system and processed (camera calibration, 

orientation, bundle adjustment – or something similar –the software does not say what 

kind of equations they use and how the 3D point cloud is being obtained) 

� Ready Photo Scene – oriented photographs and created mesh, is being send back to the 

software or to a given e-mail address, where the scene may be downloaded afterwards 

� The Photo Scene include automatically created Draft Mesh – low resolution mesh 

� Next, stitching of photos needs to be checked – some pictures may be not stitched 

correctly or be just not stitched. Stitching means here orientation or referencing 

photographs. To do the stitching at least (and only) four corresponding points (visible 

on at least 2 other pictures) has to be defined. It is also possible to unstitch the photos 

– if badly stitched, and measure the points. In the project to improve accuracy and 

reduce misalignment on every photograph at least four points has been measured. 

Since, there is no information on given accuracy of the computations, to be sure, that 

the photos are stitched as best as they could, the corresponding points were measured. 

� The Photo Scene then is being recomputed – it is sent again to the server and ready 

model is being sent back, similarly as before 

� It is possible to define scale, by referenced distance 

� Also, some lines or points may be drawn on the model – it is also done in 3dimensional 

model. 

� If the model is satisfying and all the pictures are stitched correctly, the mesh may be 

recomputed to better accuracy and resolution. “Maximum” mesh setting is the best 

one. Mesh is also always textured from these photos that are used. Figure 4.7 is a 

snapshot from the software and project file. In the image, location of cameras (location 

of taken photographs with maintained sequence of recording) may be found and 

created mesh itself as well. 

� After that the model may be exported to different files and it is possible to work on a 

model using different software. 

� The software also provide animation video creation and it allows to upload it to the 

YouTube 

43

EXPERIMENT 

Figure 4.7 Final Maximum mesh in Autodesk Photo Scene Editor 2.0 Project Photo Fly 

4.2 Three-dimensional scanning 

Data acquisition 

Artec scanner is handheld light and acquisition was done by moving scanner around the 

sculpture. In the same time view of scanned data was track, to have a view on what was 

scanned and what need to be scanned. Use of this scanner is very easy and starting/ stopping 

scan is done by pushing the button at scanner, or mouse click at software. Konica Minolta 

instead is quite heavy and bigger, and therefore it should stand on the tripod. In that case, the 

sculpture was moving; scanner was only moved to fix the view, mostly on vertical angle. 

Scanning is done by mouse click using PET software. 

4.2.1 Konica Minolta VI-910 laser scanner 

Laser scanner is quite heavy and for recording it stood on the tripod. For data acquisition 

TELE lens was used and 21 scans has been recorded. As it turned out TELE lens was not the 

best choice for this type of sculpture to cover the whole object in one scan – the object has to 

be farther from the digitizer, sometimes too far away, that the scanner could not work within 

his working distance. Therefore, MIDDLE lens was also used for improvement and 15 more 

scans were acquired. TELE lens seems to be better when it comes to accuracy, but when the 

object has to be far away the accuracy is not necessarily increasing. For the acquisition, the 

sculpture stood on the table or on the floor, to get the data from all of the sides. Scans were 

align and processed in PET software, however in many cases the software did not work, 

probably because this software is not meant to be use with Windows 7 64 bits operation 

system. Due to this problem, the scans were processed in Geomagic from raw data. 

Steps taken while using the scanner and software: 

� Plug every wire to connect laser scanner to the computer 

� Open Polygon Editing Tool Software 

� Turn on the scanner 

� Set some settings in the software if needed and find the scanner 

44

EXPERIMENT 

� Choose one scan; it is possible to set some setting there as well, but the most 

important is to set Fine Scan – to get the best results. Also filters are not required – it 

is possible to clean the scan afterwards. It is also possible to take a picture for 

texturing. 

� Move, rotate the object or the scanner or both to get the best view on the object 

� Take the scan – the scanner sets focus automatically. 

� Now save the scan and open it – clean, process and so on; or take another scan to 

cover the whole object of the interest. In the project 21 scans were acquired with 

TELE lens and 15 with MIDDLE lens 

� Next it is possible to register the scans into one coordinate system. In the beginning 

there is a need to register the scans with Initial Manual Registration tool – there one 

scan has to be defined as a base and second scan is beginning align into the first one 

and so on. It is possible to work only on one pair of the scans at the same time. To run 

the registration there is a need to define at least three corresponding points. Then the 

computational algorithm is being run. In the project, usually four or more points were 

used for better approximation. 

� After good initial registration it is time for Fine Registration – by “elements”. There 

also the base scan has to be chosen – all the scans will be registered into the chosen 

scan‟s coordinate system. Here all the scans may be chosen to register them all 

together. 

� After that the scans may be merged into one point cloud, cleaned, filtered, smoothed, 

fill holes and so on. 

� The Software automatically creates mesh from points, but it may be changed from 

view settings 

In the project steps until fine registration and merging were done, because of met the 

problems with the software. Scans were exported and imported into Geomagic and processed 

there afterwards. Also, the time was limited, final model in Geomagic was not achieved, 

although the results were quite promising. Figure 4.8 below illustrates the view of the PET 

software with merged scans from Konica Minolta scanner. 

Figure 4.8 Merged point cloud in Polygon Editing Tool from Konica Minolta 

45

EXPERIMENT 

4.2.2 Artec MHT three-dimensional scanner 

The 3D scanner is very easy to use. It is small and handheld. Scanning is being done by 

clicking the button which is on the scanner or using the software on PC. The object is being 

scanned with frames. By moving the scanner it is possible to cover the whole object even with 

a one single scan. If the digitizer is not being moved too fast, the frames are referenced 

automatically. In some cases, like in places hidden deep inside, when the object is 

complicated, there might be need to scan more times and then align the scans. In the project 

25 scans were acquired, but not all of them were used. For processing the scans Artec 

software was used, raw data were also exported and imported in Geomagic. Simple text file 

format was used for export to Geomagic. 

Global registration in Artec software when there are a lot of frames takes a lot of time and 

therefore not all the scans were used. The scanner is able to capture very dens point cloud 

with high resolution and very good accuracy, but processing all the points is very arduous task 

for PC. Raw scan may be found in the folder Artec\Scans and final model in Artec\Project 

files 

Steps taken while using the scanner and software: 

� Plug every wire to connect the scanner to the computer 

� Open Artec Scanner software 

� Set some settings in the software if needed and find the scanner 

� Click Scan and start of the scan may be initiated from the software by the “Record” or 

by the button in the Scanner. It is also possible to take pictures for texturing 

� Scan the object – rotate slowly the scanner around the object of interest 

� It is possible to take one scan and then there is more frames in one scan; or take more 

scans with lower amount of frames in each scan. It general, the author‟s opinion is that 

more scans with lower amount of the frames should be taken. Of course, it depends on 

the object, situation and so on. Nevertheless, processing seems to be better when the 

scan contains less than 500-700 frames. Also, there should not be too many scans 

neither, some computations take too much time then. 

� After acquiring the data it is time for Registration – first Rough, than Fine – for every 

scan. 

� Next, aligning the scans into one coordinate system. One scan has to be chosen as a 

reference – all the scan will be aligned into this scan‟s coordinate system. Only one 

pair may be aligned in one time, it is possible to align two scans and then another 

without quitting running this tool. The software needs at least three corresponding 

points for aligning. In the project usually four or more points were measured for better 

initial approximation. 

� After that the scans has to be register more accurately and there is a time for Global 

Registration Tool to run – it usually lead to better results, more accurate. The 

algorithm is taking every frame into the account and recomputes again, also by 

analysing relations between the frames. 

� Having the scans in one coordinate system the software provides Fusion – merging all 

scans together – it usually leads to better results. The result is usually smoother model 

and possibility of reducing of points in mesh may be met. It is hard to say exactly what 

kind of tool Fusion is, and what it exactly does for sure. Smoother model looks better 

– visually, but it may be not necessarily better, because the accuracy may be lower and 

some details may disappear. 

� Next, it is possible to filter the model, fill holes, clean and smooth it. 

46

EXPERIMENT 

� Artec software automatically creates mesh from points; it is possible to change it in 

the view settings. Screenshot from the software with smoothed model illustrates 

� Figure 4.9 below. 

Figure 4.9 Merged and smoothed point cloud in Artec Scanner software 

4.3 Geomagic Software 

The software is very powerful. It may open almost every type of format file from 3D 

scanning; it may be also point cloud or polygon or mesh from any other software. The 

software has many more tools when it comes to operations on the point cloud or mesh. Here, 

again processing huge amount of data like points or triangles needs a lot of time; however the 

results are being satisfactory. Scans from three-dimensional scanning were processed from the 

beginning using this software. The results from photogrammetry were also imported, but the 

only thing which was done is a bit of final mesh processing. 


� Import the scans 

� Aligning the scans (if not aligned). First by defining corresponding points – at least 

three – Manual initial registration. Only one scan may be aligned to another at the 

same time, however without exiting the tool and by choosing “next”, next scans may 

be aligned to already aligned ones. 

� Next, run Global Registration – accurate registration of all scans into one coordinate 

system; 

� Then “execute overlap” may be chosen and this option usually improves the results. It 

is a command after Global Registration and applies a slight bend the objects to move 

them into a more perfect registration. 

� Then the scans may be merged into one point cloud 

� Later on, the scans may be filtered, cleaned and so on. Cleaning the scans should be 

done before alignment and merging – it usually improves the results, by for instance 

removing the unnecessary points. Also some noise may be removed before merging; 

but this may be done afterwards. In the project both ways were tested and some noise 

47

EXPERIMENT 

was removed before merging but most of occluded points were removed afterwards, 

by selecting tool: “outliers” and “disconnected components” 

� Next, the mesh – TIN may be created. Running this tool it is also possible to use some 

filters. Those filters mostly smooth the surface and remove some noise. Smoothing is 

maybe not the best solution for the purpose of the project, but on the other hand model 

results with a lot of “bad” triangles which have to be repaired, and at the end, the 

resulting model is not the best neither. 

� The resulting model may be here filtered, cleaned, smoothed, the holes may be filled 

in and so on. In the project, most of the tools were used. First removing the noise with 

the least smoothing type and choosing “aggressive-curve” style to preserve curves in 

the model. Also, removing spikes smooths the model and make it nicer. For every type 

of model different amount for reducing should be used. If mesh has a lot of triangles 

the number for smoothing may be bigger. Some bad triangles however had to be 

removed manually. Holes were mostly filled with “Fill All” function, but the bigger 

ones were filled separately, and one by one. 

� Having a model it is also usually recommended to check the model with Mesh Doctor 

and repair the triangles. This tool was also used in the project, it is very important to 

receive right surface, the tool also may improve the results. 

� In the Geomagic Studio or Wrap it is possible to texture the model from pictures, 

though in the project, only Qualify was used and therefore only the colour of texture 

was being changed. 

Figure 4.10 below represents screenshot from the software after global registration and on the 

model, deviations on points are displayed. 

Figure 4.10 Registration of point clouds in Geomagic; model of deviations 

48

RESULTS, COMPARISSON AND ANALYSIS 

5 RESULTS, COMPARISSON AND ANALYSIS 


5.1.1 Camera calibration (PhotoModeler Scanner and Topcon ImageMaster) 

In order to get good results – accurate, from photogrammetric method, a good camera 

calibration is required. Because, commercial camera, non-metric was used in the project, 

calibration was done, to get all the necessary parameters of camera interior orientation and 

distortions of the lens. In such cameras PhotoModeler scanner or ImageMaster could be used 

for this purpose. The companies give calibration field to have all measurements and 

calculations automatic. It is very convenient and even people who do not have any 

photogrammetric background may do this. It is also possible to use different test field, but 

then some measurements have to be done manually and also taking appropriate photographs 

may be difficult to achieve required coverage. 

Some parameters are possible to get from EXIF information from the image file. EXIF – 

Exchangeable image format, is a standard that specifies the formats for images and ancillary 

tags used by digital camera. Having this on mind, the softwares mentioned before may treat 

some parameters as initial, and / or maybe fixed. For instance, ImageMaster may use Image 

resolution obtained fully automatic, but it may also be specified by the user by giving pixel 

size and image sensor size. From this point of view, it may be suspected that even if full 

automatic calibration is chosen, these parameters are treated as fixed and might be taken from 

EXIF information. It may be also suspected from calibration results, where no parameters 

considering image sensor size are shown. 

When it comes to accuracy, the results - numbers that the software gives us look quite good. 

In PhotoModeler last error from the last iteration is 0,847; Overall RMS is 0,810pix with 

maximum equal 0,463pix and maximum RMS 0,317pix, where the maximum vector is 

0,0404mm, what can be acclaimed as a good result of adjustment. ImageMaster gives 

standard deviation, which is equal 0,9842mm and maximum residual which is 2,6474mm. 

The results are also good, but maximum residual might be reconsidered for the very accurate 

measurements. It is quite hard to compare the results, since the softwares give slightly 

different deviations or different unit. 

When it comes to values of parameters, they are also different. Especially when it comes to 

Focal length, and difference is about 1,4mm, which is quite a lot for that feature. Also, when 

it comes to principal point, in X- direction difference is 0,9mm, but a bit smaller in Z – 

direction – 0,5mm. Though, the parameters of camera interior orientation are highly 

correlated, and when the software uses different image sensor size, for example the focal 

length may differ. Also, parameters of lens distortion are correlated and both softwares have 

slightly different results. Therefore, it is hard to say, which software gives more accurate 

parameters. 

When it comes to the user, it is easier and faster to use ImageMaster, because the software 

requires only five photographs for calibration, when PhotoModeler needs twelve. When it 

comes to the results and accuracy, there might by suspicion that PhotoModeler will result in 

better adjustment. Having more photographs taken from different angles may improve 

computations, may give better approximation and adjustment of the parameters, because more 

49


observations are given to the mathematical model. Table 5.1 below represents results of 

camera calibration from both softwares. 

From the user side, both calibration projects are easy, most of processing is being done 

automatically when test field from software applied. Figure 5.1 and Attachment A. 2 

represents in accordance results of camera calibration from Topcon‟s and PhotoModeler‟s 

software. 

Table 5.1 Comparison on results of camera calibration using photogrammetric softwares 

Application PhotoModeler Scanner Topcon ImageMaster 

Number of photographs used 12 5 

Interior orientation parameters: 

Focal lengths f 29,361075 mm 27,999864 mm 

Principle point Xp 18,020201 mm 17,081758 mm 

Principle point Yp 11,789349 mm 11,314753 mm 

Lens distortion parameters: 

Radial distortion K1 1,419 e-004 1,538941 e-004 

Radial distortion K2 -1,709 e-007 -2,057164 e-007 

Tangential (decentric) distortion P1 -6,230 e-006 -6,622480 e-006 

Tangential (decentric) distortion P2 -1,368 e-005 -0,8847591 e-005 

Format width Fw 35,761454 mm No info 

Format height Fh 23,799800 mm No info 

Pixel size Xr/Yr 8,4 µm 8,4 µm 

Standard deviation 0,847 – last error 0,9842 mm 

Maximum residuals 0,463 pix (0,0039 mm) 2,6474 mm 

Figure 5.1 Results of camera calibration from Topcon ImageMaster 

50


5.1.2 Photogrammetric project concerning modelling of the sculpture (PhotoModeler 

Scanner and Topcon ImageMaster) 

When it comes to the terminal project, bundle block adjustment of photographs of the 

sculpture and also creating point clouds from photographs the situations is being changed. Of 

course, in both softwares: PhotoModeler Scanner of ImageMaster, camera calibration made 

before is being used for the project. 

PhotoModeler Scanner is able to mark all the circular points automatically, or coded points 

designed by the company. Nevertheless there was a slight problem with automatic referencing 

between them. At least six points in each photograph had to be referenced manually at first. 

The software needs approximate values to be able reference all the points automatically. 

Referencing and marking points does not have to be done in respect to photo pairs. Number of 

measured point is set automatically and link between the points (corresponding on the other 

photograph) specifies the correspondence. Points, if the automatic marking is used, are 

measured with sub-pixel accuracy. Also, when a point is not marked, it can be marked 

manually by the user, by specifying rectangular area where the circular point is. Afterwards, 

the project had to be “processed” – it is realising computations for orientation, bundle block 

adjustment. After that, having „initial‟ orientation, automatic referencing could be used and all 

marked points are being referenced. 

For some reasons, every stripe had to be processed separately. A stripe here means that few 

photos were taken from lower or higher position than others. The software could not manage 

to compute all of them together in the beginning. The result was error message and software 

was not able to compute anything at all, or very high residuals were seen on the other stripe. 

But, when every stripe was treated separately – results and accuracy was very good and after 

then, all photographs were processed and oriented together and final results of computations 

were satisfactory. For some reasons, software refuses to compute parameters of orientation on 

the beginning, but after “initial” orientation of every stripe, it worked completely fine, even 

though nothing was changed in the position of points or links between them. It may be 

because the software requires better approximation of initial parameters for computations, but 

any error message did not give any clue of that problem. In the project, 120 points were used 

in total for bundle adjustment. Having more points may give better accuracy, better 

adjustment – more accurate. It may be approved, because overall RMS error is 0,102 pixels, 

where the maximum residual is 0,544 pixels. Also, maximum RMS error is 0,255 pixels and 

maximum vector length is 0,271mm, which can be perceived as accurate results. 

In ImageMaster photo pairs should be created from the beginning. Marking and referencing 

control points could be done in a single photo or in photo pair, at this stage it does not have 

any difference. It has to be mentioned that the same photos and the same amount were used 

using both software. Marking could be done together with Referencing, which is done by 

specifying a point with the same index number. Circular points or corners may be measured 

with sub-pixel accuracy as well, but in Topcon‟s software automatic measurement means only 

auto measure but by approximate click at the point. Because every point has to be clicked, 

only points on the sculpture and in the corners were used for bundle block adjustment, not all 

of them, from 7 to 19 tie points were used in one photograph. Computational part went very 

well, very small errors and residuals and all pictures were processed together without any 

problems. Maximum Residual, parallel is 0,21pixel 0,26mm in Image Coordinate System. 

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Next stage was to idealize project and process again after then in PhotoModeler. Idealize 

project means to transform images and remove distortions caused by the lens also it respects 

position of principal point and non-squared pixels. This process is recommended to run and 

the project should be “re-processed” in order to get better – more accurate results of 

orientation. 

In ImageMaster opening stereo pair is stereoscopic view initiate computations which 

transform images and display them stereoscopically (special equipment needed). It is a bit 

similar process that “idealizing” in PhotoModeler Scanner, but here images have to be also 

transformed in a way that stereoscopic view is possible to achieve. 

Next, the area for DSM creation has to be specified, at least in one photograph 

(PhotoModeler), or one photo pair in stereo mode in ImageMaster. It is needed especially to 

reduce time for computations, because then the algorithm uses the selected area for image 

matching and point generation. 

After then, the setting for DSM creation needs to be chosen. In ImageMaster there is not so 

many available options to choose, only filter (mean or median and eventually e.g. breaklines); 

how many specified photo-pairs should be used (from defined before), and which photographs 

should be used as a texture. In PhotoModeler instead every combination of photo pairs could 

be used, however not every pair will produce good mesh or any mesh at all. The software 

gives opportunity to select the “best pairs” , what is done automatically. Criteria here are: 

height-to-base ratio, angle between the photos and residuals – quality. There are also 

additional settings that can be changed during DSM creation. It may be a distance 

above/below the surface, sub-pixel sampling, matching area size and texture quality. In 

PhotoModeler at the same time the point cloud may be processed, merged into one surface, 

triangulate and smooth, but it may be done afterwards as well, which is rather recommended. 

It is better to choose lower resolution for point generation and check if the created point cloud 

represents good surface and then change the resolution to higher. It is also better to check the 

surface before modifying the points, filtering and triangulating. It may save time, because 

sometimes the chosen settings may give wrong surface and therefore there is no sense of 

waiting for a very long time for bad result. In Topcon software the result is already 

triangulated surface. 

In both software creation of dense high resolution DSM needs a lot of time. In both cases 

there were some parts where the algorithms created very good surface, but in some areas very 

bad. The sculpture is shiny and there were always some parts which reflect the light. There 

was no possibility to avoid this situation. What is more, the sculpture is very detailed and has 

places hidden deep inside which are covered by other parts of the object and therefore more 

photographs should be taken, to cover the entire object. If more photographs, the more time 

needed for computations and image matching and DSM creation. If the object would not be 

shiny photogrammetry method gives very good results, very little noise, but in this case it was 

very hard to get the whole model and model resulted with high amount of noise and 

mismatch. Topcon‟s software was used only in Trial version and therefore, the final model 

was not achieved, because of time-limitations. 

Figure 4.3 in previous section illustrates textured model in ImageMaster using only one 

photo-pair. In PhotoModeler final model was not achieved neither, because long time was 

needed for point cloud generation and model resulting with big amount of noise. Figure 5.2 

and Figure 5.3 illustrates the result from PhotoModeler Scanner. The first one is a mesh using 

52


three photographs – four photo-pairs and second one is mesh using more photo-pairs but 

smaller area. The aim was to test the method if it will produce the good surface at all. These 

results are also from photographs, where dust-spray was used and there was less reflection. It 

is possible to see that in some places there was more noise and mismatching. Importing the 

results to the Geomagic did not improve the results so much and therefore the more results 

and omitted. Table 5.2 below compares the software – the main steps and features in respect 

to used object and author‟s opinion. 

Table 5.2 Comparison of photogrammetric software: ImageMaster, PhotModeler Scanner 

Step PhotModeler Scanner Topcon ImageMaster 

Camera calibration, 

image acquisition, 

processing 

Bundle block 

adjustment, control 

points marking, 

referencing, 

processing 

DSM creation, 

modification, view 

+ automatic marking, referencing and 

computation 

- more photographs needed – more time for 

acquisition, but may produce more accurate 

results 

- hard to take picture with required coverage 

+ automatic marking all circular or coded 

points with sub pixel accuracy 

+ automatic referencing (if „initial‟ orientation 

firstly computed) 

- error during processing entire set of 

photographs, the software probably needs 

better approximation of values and refuses to 

process the entire project, or big error is 

coming out, sometimes few photographs has to 

be processed before processing entire set 

+ easy specification of area of interest 

+ selecting useful photo pairs 

- time needed for generation of point cloud and 

triangulated surface 

+ easy modification of DSM and triangulation 

+ texture available from view settings 

- inconvenient view changing: rotation, moving 

and panning 

53 

+ automatic marking, referencing 

and computation 

+ only 5 photos needed – faster, but 

might produce less accurate results 

+ easy image acquisition with 

software requirements 

- no automatic marking control 

points 

+ automatic only by click by means 

of sub pixel accuracy on circular 

point of corner 

- no automatic referencing 

+ processing entire set of 

photographs 

- difficult specification of area of 

interest – (polygon is created on 

photo pair in stereo mode and is 

visible on every photo pair, when 

round object, difficult to specify 

proper polygon) 

- photo pairs specified from the 

beginning (good and bad, depends 

on purpose) 

- time needed for generation of 

triangulated surface (and only 

surface, without point cloud) 

- not much tools for DSM 

modification 

+ texture available from view 

settings 

+ easy view changing 

Exporting + easy and fast export, also with texture + easy export, also with texture 

- time needed for export


Figure 5.2 Textured model from PhotoModeler Scanner; sculpture was sprayed with dust 

Figure 5.3 Shaded model from PhotoModeler Scanner, representing “hair”, 1mm resolution 

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5.1.3 Autodesk Project Photofly Photo Scene Editor 2.0 Software 

This software the author treats separately because of different features of the application. It is 

open source, very easy to use and does not require any background; the only knowledge 

which is needed is introduced by the Autodesk on the website. For commercial use it is very 

good software, produces quite good dense mesh without long arduous work in the office. 

Only few (at least 4 point corresponding) points are measured in the pictures if needed for 

stitching them and everything is computed by the server and ready surface is being sent back. 

The only thing that would be appreciated is the accuracy assessment and capability to choose 

higher resolution, or at least some information about it. Also, in some cases, some editing of 

the mesh could be improved. Probably for most of the users it is enough, for this project it 

was not. The mesh which was created looked very good, but there were few places where the 

surface was computed wrongly, it may be caused also by the reflection and the shape of the 

object. After all, having on mind that the software if freeware and everyone can use it, the 

entire impression is very high and for many cases this accuracy and resolution is enough. 

It is good tool, for modelling and also make CAD model – wire frame, because of capability 

of drawing lines and so on and export CAD file. This file includes only lines of points, not 

raw point cloud. There is also a very interesting tool available in the software – making video 

file and put it to the YouTube. The video file was also made during the project and may be 

found in folder Autodesk\Exports\Video. Figure 5.4 illustrates the model from Autodesk‟s 

software and Figure 5.5 illustrates the same model, but improved using Geomagic and without 

the texture. 

Figure 5.4 Textured model from Autodesk Project PhotoFly 2.0 

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Figure 5.5 Model from Autodesk Project PhotoFly; converted and improved in Geomagic 

5.2 Three-dimensional scanning 

Scanners used in the project are very different. For instance Konica Minolta works with a bit 

longer distances. When it comes to light, Konica uses laser – (actually three scans, where 

output is actually one scan, which is average of these three scans). Laser – actually horizontal 

plane of laser is moving from up to down, by using rotating mirror. Artec instead uses flash 

bulb - no laser; a light pattern of horizontal lines. Artec, since it is handheld scanner, and 

pattern is very small, scanning is done by acquiring single, small frames (up to 15 per 

second), which are being referenced online - through tracking system. One scan is a set of 

these frames. Key frames are automatically defined by the software and those build a 

skeleton. In respect to key frames all of frames in scan are registered into one complete scan. 

If some scans are badly referenced they might be moved to a new scan. 

In both softwares, that the digitizers use, aligning scans is easy and require three 

corresponding points to align two scans. Specific control points or spheres are not required. 

Measuring -marking corresponding points does not have to be very accurate neither. In both 

cases situation of initial alignment is very similar. In PET only two scans can be aligned at 

one time, in Artec also, but the aligned scan may be marked as align and added to the model 

of “aligned” scans and aligning next scans is becoming easier, because there is visible bigger 

area of object to align. 

56


Next, when initial aligning is done, fine registration may be computed. In PET it may be done 

on two scans, a few or all of the scans by applying “Fine registration”. Situation in Artec is 

similar, any amount of scans may be chosen for accurate registration. In Artec it is done by 

“global registration”.. There the algorithm recomputes every frame separately; it computes 

correlations between every frame. When there is a lot of scans and frames it may take a very 

long time. 

In PET registered scans are being merged and then model may be improved by applying some 

modifications like filtering, smoothing or filling holes. In Artec, the scans, all frames are 

being “fused”. There is visible improvement of model after the fusion – the model is 

smoother. After then, some cosmetics may be done in the software. No matter what kind of 

scanner of software, it is recommended to remove points from background, before alignment, 

because it may produce bad results, due to that algorithms use all points and background on 

every scan may differ. 

PET software is not fully compatible with 64 bit systems and Windows 7. Probably that was 

the reason of some problems that were met during using the application. The software became 

grey in some cases and mostly it just refused to work, by showing error messages. Because of 

this, model was done only until merging all the scans. The rest has been done using Geomagic 

software. Although the final model was not achieved (because of time limitations), it was 

looking quite promising. 

Artec is able to use full, or most of performance that computer gives. It still needs some time 

for computation, if a lot of data. However, the final model was made. One problem was met 

there, in some places, where the noise occurred. It was irremovable by any filters, and 

therefore smooth brush has to be implemented. Moreover, the brush does not work good 

enough, because it soothed the area around and it might smooth some surfaces in unexpected 

way. At the end the model looks good, omitting few places. The model is very detailed. 

Figure 5.6 illustrates the final model from Artec Software. 

When it comes to number of scans which was used in the project, from Konica Minolta 20 

scans with TELE lens was used and 24 with MIDDLE. In PET all of them were merged. In 

Geomagic not every scan was used, because very few of them were not aligned properly. 

Using Artec scanner about 17 scans were taken. Each scan contains from 207 to 722 surfaces 

(frames) and about 1090 to 23014 polygons in one frame. In Artec software only few scans 

were used for modelling, because Global Registration for all frames would take too much 

time. In Geomagic instead all of them were taken into account, but few of them were skipped, 

because of miss-alignment with others. 

Accuracy in Artec software is very hard to define. The company gives only resolution which 

is up to 0,5mm and accuracy, which is 0,2mm. After global registration the Quality which 

shows the software was 0,2mm. It is assumed it is accuracy of alignment the scans (frames) 

(residuals between scans). Accuracy for Konica Minolta scans in PET software can be given 

in registration error. For tele lens average error was 0,527 with sigma 0,428. For middle lens 

average error was 0,348 and sigma 0,310. It is visible that alignment was slightly better with 

middle lens. It is probably connected with the distance to the sculpture. When tele lens was 

used, this distance has to be very close the limitation of the scanner. The object was quite far 

away; otherwise not entire surface was possible to be seen on the screen and scanned. 

The model in Artec resulted in 5 943 308 polygons, where in PET model contains 967 131 

polygons. Artec has about six times more polygons in mesh. 

57


Figure 5.6 Model from Artec MHT scanner and Software 

5.3 Geomagic Software, modelling, post-processing software 

In the end, from every softwares, the results – point clouds, surface or raw scans were 

imported to Geomagic. The software is able to handle a lot of different file formats. It is 

possible to process raw scans from the beginning, align them and so one, what was done. The 

results of alignment look better. The software also needs a lot of time for some computations 

if there is a lot of data, heavy point clouds; however some of them seem to be faster. It is sure 

that from a technical point of view, it was better to use Geomagic than PET when it comes to 

Konica Minolta software. 

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In the end, in author‟s assessment Geomagic produced the best model, the most detailed, 

which was the aim of the project. In connection to data from Artec and this software results 

seem to be the best. It may be compared with model made in Artec scanner as well. Konica 

Minolta produced also quite a good model, but fewer points make it more smoothed. Also, 

hidden places in the sculpture were very difficult to get in comparison to Artec scanner. With 

smaller and handheld scanner it is easier to get data in hidden areas, also working distance is 

important there. Table 5.3 below shows comparison of main features of the softwares from 

scanning and Geomagic: from data acquisition to final model; in author‟s assessment. Figure 

5.7 illustrates 2D image from Geomagic, where data from Artec scanner were used. There is 

also Table 5.4 where the results from scanning are compared, processing in Geomagic. 

Table 5.3 Comparison on scanning systems: Artec, Konica Minolta, processing in Geomagic 

Stage Konica Minolta, PET Artec, software Geomagic 

Data 

acquisition 

+ fast scan 

+ not so much noise 

- hard to get hidden areas 

- distance of working 

- heavy and big instrument 

- TELE lens for better accuracy 

can be used only with small 

things, due to working distance 

and size of the view 

Alignment + good alignment without special 

points 

Registration + final registration gives quite 

good result 

Merging - merging scans may give holes, 

even if the data were existing 

(probably because of 

Surface tools, 

editing 

misalignment) 

+ fast scan with a lot of 

data 

- losing tracking when 

rotated too much or too 

fast 

- sometimes too much 

data, which produce a lot 

of noise 

+ distance of working 

+ light and very easy to 

use 

+ easy to get all 

necessary data 

- in some cases 

misalignment of frames 

in one scan 

+ easy alignment of 

scans, without special 

points 

+ fine and global 

registration which gives 

good results 

+ fusion gives better 

model 

No info + easy use of filters, 

which mostly give good 

results and model is 

improved 

- some noise is difficult 

to remove, especially if 

close to the surface 

59 

Geomagic is not designed for 

any data acquisition, only 

processing 

+ easy, do not require special 

points 

+ good results 

+ good results, option usually 

improve results 

+ no reduction/ addition/ 

edition of data while running 

merging tool, all scans/ data 

are just merged 

+ a lot of tools, filters for 

model improvement, which 

gives better model 

- in some cases difficult to 

remove noise without proper 

surface


Figure 5.7 Model from Artec MHT scanner, but data processed in Geomagic, which is 

perceived as the best one. 

Table 5.4 Comparison on results of alignment scans in Geomagic software 

Konica Minolta Polygon Editing Tool Artec 3D Scanner 

Alignment & global registration: 

Average distance 0,568 mm 0,240 mm 

Standard deviation 0,304 mm 0,210 mm 

Maximum deviation 0,688 mm 0,614 mm 

Total scan used 19 (tele lens) 

23 (middle lens) 

17 

Number of triangles (final model(s)) 967131 polygons 5943308 polygons 

60

6 DISCUSSION AND CONCLUSION 

DISCUSSION AND CONCLUSION 

The best model was received using the most accurate scanner. Some companies advertise 

their projects as the best, but in this case Artec scanner turns out to be the best for the project 

purpose. Artec Company also has even a more accurate scanner, than it was used in the 

project. It is version S, which is capable to acquire 0,2mm resolution with 0,005mm accuracy, 

where distance of working is shorter. The only disadvantage is that it does not acquire texture. 

It is assumed that this scanner would give the best results, because of better accuracy and 

resolution. Unfortunately, this scanner was not available for tests. 

Artec software is able to create a very good model from the scanned data. Some 

computations took a lot of time e.g. Global Registration and therefore only the necessary 

scans should be used for post-processing. 

Geomagic seems to be better software for processing, it allows to have bigger impact and 

control what is actually being done with the data. The user may specify more accurate what 

kind of smoothing algorithms he/she needs and factor of smoothness she/he wants. It is 

possible to reduce the amount of points or triangles even while importing the files. Also, it is 

very easy to remove some points – in general. The tool, which was very appreciated and used 

a lot, was Select- outliers, because it very efficiently reduces noise. The “disconnected 

components” tool was also used for reducing unwanted points. It is very difficult to remove 

points - noise, which are close to the real surface and there the tool “select outliers” worked 

very well. 

“Noise reduction” tool used on points, gives also a possibility to select outliers and remove 

them. The algorithms move points to the average position and make the surface smoother, 

which was also a very good tool and used as well. A very smooth surface was not the aim of 

the project; however, in order to remove noise the tool was appreciated. While smoothing, 

some details may disappear, but when the aggressive-curve tool is applied it is not changing 

so much the curves. On the other hand, Noise reduction tool has to be used, in order to 

remove noise, which also has big impact on the surface and created mesh was not 

representing the real object. There should be some balance, because without smoothing, 

model contains a lot of noise and does not render the object in a good way. When the model is 

smoothed it looks more like a real object, noise is removed, but some small details may 

disappear. 

But, Geomagic software does not smooth the surface from the beginning, what Artec probably 

does during the Fusion. This especially makes Geomagic better software. Moreover, if more 

points used for modelling in Geomagic and more triangles are created while “Wrapping” 

(meshing, triangulation) the more detailed model will come out. Even if the Noise reduction 

tool or smoothing (low smoothing level) is being used, the details still remain visible on the 

model. Disadvantages here may be that the software needs more time for same computations 

and also the project file is getting bigger. 

Konica Minolta VI-910 turns to be quite a good laser scanner, however for this purpose it was 

very difficult to get the whole data, and the model contained a lot of holes. Also, in 

comparison to the Artec scanner it has slightly worse accuracy and lower resolution, which 

was the main determining feature. From Table 5.4 and section above, it is possible to see that 

Artec resulted with 0,210mm standard deviation and 0,614mm with maximum deviation 

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between aligned scans, where Konica Minolta resulted adequately 0,304mm and 0,688mm. 

The values are not so much different, but bigger difference is in Average distance between 

scans which is in Artec 0,240mm and 0,568mm in Konica Minolta, which tells us that 

alignment here was worse. A comparison was made in Geomagic software. But, these 

numbers may not describe that the model will be better or worse or the model will have more 

or fewer details. It is some kind of assessment, but cannot be treated as the most important 

factor. Standard deviation may be bigger, but visually the scans may be aligned better. Also, if 

the scans contain a lot of noise, even if the alignment of them looks very good from the 

numbers, the model may not be so accurate. 

The author has the impression here that Konica Minolta gives scans with less amount of 

noise, but the resolution seems to be worse than using Artec. On the other hand, if a lot of 

scans would be acquired the resolution will somehow increase while merging all the data and 

the model may contain a lot of details. Still, during data acquisition using Konica Minolta, it 

was hard to get all the data – there is a lot of holes, but it may not be the worst problem and 

those holes may be filled afterwards. Konica Minolta might also result in detailed model, 

rather slightly worse than from Artec. Yet, because of time limitations the final model was not 

achieved. 

For the purpose of the project, texture is not necessary. It would be nice to have one, in case 

you want to show people a digital model on the screen, to give more natural look. However, 

the model is needed to make a real replica, to use it for printing. In that case only 3D 

information is needed, and therefore texture may be skipped. 

Photogrammetry method works very well for modelling, when not high resolution is required, 

because waiting for point cloud takes a lot of time. Also, if the object is not glass, or any 

surface that is shiny and reflects the light, the method is proper. In the project the sculpture 

was a bit shiny and in some cases image matching did not worked well enough and software 

produced a lot of noise. Photogrammetric softwares still need some improvement when it 

comes to time of computation, especially when high resolution required. What is more, the 

software should be made in a way that would be able to make use of maximum performance 

that the computer gives. Or, at least the software should has an option, where it could be 

chosen or specified, what kind of PC is being used and how much of processor and memory 

could be used. Artec software is able to use all of the processor‟s cores, and also Geomagic is 

able to make use of most of the available performance. The rest applications that have been 

tested do not use all the power that PC may give. 

Autodesk software is also based on photogrammetry, but works differently. It is open source 

and it is very easy to use. Everyone is able to use this software, without mostly any 

background knowledge. The application produces quite good mesh, with texture and in many 

cases it is enough. Nevertheless, for the project the model was not too accurate and resolution 

was too low. 

Software for DSM creation or edition, manipulation point clouds still needs some 

improvements. Some works better than the others, however there should be options which 

could be changed according to computer performance. Everyone may use a different PC and 

in the project the workstation was very good. During the computations the system worked 

slowly, or it was possible to discover that not every processor core was working. Not entire 

available memory was used either. Still computations took too much time, while the potential 

of PC was not used properly. Companies need to improve this field and give opportunity to 

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change performance settings in respect to the used computer, also in respect to used operation 

system, especially x64bits, which gives more capability. 

In spite of all the problems which were met, the final model was done, the one that was giving 

the best results – from Artec MHT scanner. Artec and Geomagic software was used for this 

purpose, however in author‟s opinion Geomagic resulted in a better model. Figure 6.1 

represents this model. Also, 3D PDF file was also made in Geomagic and is possible to find 

that file in folder Geomagic\Artec\Exports\Files. The produced file is not as heavy as VRML 

file and the model may be viewed in 3D mode, rotate, etc. It is also possible to change the 

light and model display. Also, any other exported 2D images or 3D files and more 3D PDF 

files may be found on the DVD attached to the report. 

At the end of the report, in figure Figure 6.2 and Figure 6.3 visual comparison of some 

detailed area may be found. The first one is more concentrated on “hair” and a face of the 

Archbishop. It is easy to notice that the model from Artec gives more details, where Autodesk 

– significantly less. Also, probably if the model from Konica Minolta was finished it would 

probably look also quite good, but here a lot of small holes are visible. A similar situation 

may be found on the second figure, but there the view is more concentrated on more “sharp 

edge” of the collar. 

63


Figure 6.1 Final model from Geomagic, using Artec MHT data 

64


Figure 6.2 Visual comparison of model – more detailed part of the sculpture – “hair”; top left Geomagic - “Artec”, top right Geomagic - 

“Autodesk”, bottom left Geomagic – “Konica Minolta”, bottom right “PhotoModeler Scanner” 

65


Figure 6.3 Visual comparison of model – more sharp part of the sculpture – “collar”; top left Geomagic - “Konica Minolta”, top right Geomagic - 

“Autodesk”, bottom Geomagic – “Artec” 

66

REFERENCES 

REFERENCES 

Akca, D., Gruen, A., Alkis, Z., Demir, N., Breuckmann, B., Erduyan, I., Nadir, E., 2006. 3D MODELING OF 

THE WEARY HERAKLES STATUE WITH A CODED STRUCTURED LIGHT SYSTEM, in: Maas, H.-G., 

Schneider, D. (Eds.), ISPRS Commission V Symposium 'Image Engineering and Vision Metrology'. 

International Society of Photogrammetry and Remote Sensing, Dresden, Germany, pp. 14-19. 

Akca, D., Grun, A., Breuckmann, B., Lahanier, C., 2007. HIGH DEFINITION 3D-SCANNING OF ARTS 

OBJECTS AND PAINTINGS, in: Gruen, A., Kahmen, H. (Eds.), Optical 3-D Measurement Techniques VIII, 

Zurich, Switzerland, pp. 50-59. 

Akca, D., Remondino, F., Novák, D., Hanusch, T., Schrotter, G., Gruen, A., Recording and modeling of cultural 

heritage objects with coded structured light projection systems, pp. 1-7. 

(http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.67.5893&rep=rep1&type=pdf) 

Akca, D., Remondino, F., Novák, D., Hanusch, T., Schrotter, G., Gruen, A., 2007. Performance Evaluation of a 

coded structured light system for cultural heritage applications, in: Beraldin, J.-A., Remondino, F., Shortis, M.R. 

(Eds.), Videometrics IX, Proc. of SPIE-IS&T Electronic Imaging, San Jose (California), USA, pp. 1-12. 

Alyilmaza, C., Alyilmaza, S., Yakarb, M., 2010. MEASUREMENT OF PETROGLYHPS (ROCK OF ARTS) 

OF QOBUSTAN WITH CLOSE RANGE PHOTOGRAMMETRY, in: Mills, J.P., Barber, D.M., Miller, P.E., 

Newton, I. (Eds.), Proceedings of the ISPRS Commission V Mid-Term Symposium 'Close Range Image 

Measurement Techniques'. International Society of Photogrammetry and Remote Sensing, Newcastle upon Tyne, 

United Kingdom, pp. 29-32. 

Atkinson, A.D.J., Blasco, J.J.d.S., Bejarano, J.d.M., 2010. APPLIED 3D PHOTOGRAMMETRIC STUDIES 

FOR THE HISTORICAL HERITAGE OF EXTREMADURA (SPAIN), in: Mills, J.P., Barber, D.M., Miller, 

P.E., Newton, I. (Eds.), Proceedings of the ISPRS Commission V Mid-Term Symposium 'Close Range Image 



Atkinson, K.B., 1996. Close Range Photogrammetry and Machine Vision. Whittles Publishing., Caithness, 

Scotland, UK. 

Bache, S.N., 2003. Scanning av skulptur på Nidarosdomen. Vinn Design, Oslo, Trondheim, pp. 1-4. 

Balestrinia, E.F.d., Guerra, F., 2011. NEW INSTRUMENTS FOR SURVEY: ON LINE SOFTWARES FOR 3D 

RECONSTRUCTION FROM IMAGES; ISPRS Commission V - WG 4; Poster Session, in: Remondino, F., El- 

Hakim, S. (Eds.), Proceedings of the 4th ISPRS International Workshop 3D-ARCH: "3D Virtual Reconstruction 

and Visualization of Complex Architectures". International Society of Photogrammetry and Remote Sensing, 

Trento, Italy, pp. 1-8. 

Barazzetti, L., Remondino, F., Scaioni, M., 2010. AUTOMATION IN 3D RECONSTRUCTION: RESULTS 

ON DIFFERENT KINDS OF CLOSE-RANGE BLOCKS, in: Mills, J.P., Barber, D.M., Miller, P.E., Newton, I. 

(Eds.), Proceedings of the ISPRS Commission V Mid-Term Symposium 'Close Range Image Measurement 

Techniques'. International Society of Photogrammetry and Remote Sensing, Newcastle upon Tyne, United 

Kingdom, pp. 55-61. 

Barba, S., Fiorillo, F., Coder, P.O., D‟Auria, S., Feo, E.D., 2011. AN APPLICATION FOR CULTURAL 

HERITAGE IN ERASMUS PLACEMENT. SURVEYS AND 3D CATALOGUING ARCHAEOLOGICAL 

FINDS IN MÉRIDA (SPAIN), in: Remondino, F., El-Hakim, S. (Eds.), Proceedings of the 4th ISPRS 

International Workshop 3D-ARCH: "3D Virtual Reconstruction and Visualization of Complex Architectures". 

International Society of Photogrammetry and Remote Sensing, Trento, Italy, pp. 1-6. 

Barnett, T., Bryan, P., Chandler, J., Case study: Recording Prehistoric Rock Art; Pre-historic photogrammetry 

and laser scanning, pp. 1-2. (http://www.terrageomatics.com/pdfs/Rock%20Art%20-PI-3000.pdf) 

Blais, F., 2004. Review of 20 Years Of Range Sensor Development. Journal of Electronic Imaging 13(1), 231- 

240. 

67

REFERENCES 

Blake, W.H., 2010. WHAT IS THE FUTURE OF METRIC HERITAGE DOCUMENTATION AND ITS 

SKILLS?, in: Mills, J.P., Barber, D.M., Miller, P.E., Newton, I. (Eds.), Proceedings of the ISPRS Commission V 

Mid-Term Symposium 'Close Range Image Measurement Techniques'. International Society of Photogrammetry 

and Remote Sensing, Newcastle upon Tyne, United Kingdom, pp. 98-102. 

Bonfanti, C., Chiabrando, F., Spanò, A., 2010. HIGH ACCURACY IMAGES AND RANGE BASED 

ACQUIRING FOR ARTISTIC HANDWORKS 3D-MODELS., in: Mills, J.P., Barber, D.M., Miller, P.E., 




Brutto, M.L., Spera, M.G., 2011. IMAGE-BASED AND RANGE-BASED 3D MODELLING OF 

ARCHAEOLOGICAL CULTURAL HERITAGE: THE TELAMON OF THE TEMPLE OF OLYMPIAN ZEUS 

IN AGRIGENTO (ITALY), in: Remondino, F., El-Hakim, S. (Eds.), Proceedings of the 4th ISPRS International 

Workshop 3D-ARCH: "3D Virtual Reconstruction and Visualization of Complex Architectures". International 

Society of Photogrammetry and Remote Sensing, pp. 1-8. 

Chmielewski, K., Szulwic, J., Niemetryczne zdjęcia cyfrowe w fotogrametrii bliskiego zasięgu w systemie 

Topcon PI-2000, Sesja Jubileuszowa 60-lecia Katedry geodezji Politechniki Gdańskiej, pp. 1-8. 

(http://www.terrageomatics.com/pdfs/PI-3000%20Polish.pdf) 

Deseilligny, M.P., Clery, I., 2011. APERO, AN OPEN SOURCE BUNDLE ADJUSMENT SOFTWARE FOR 

AUTOMATIC CALIBRATION AND ORIENTATION OF SET OF IMAGES., in: Remondino, F., El-Hakim, 

S. (Eds.), Proceedings of the 4th ISPRS International Workshop 3D-ARCH: "3D Virtual Reconstruction and 

Visualization of Complex Architectures". International Society of Photogrammetry and Remote Sensing, Trento, 

Italy, pp. 1-8. 

Earl, G., Beale, G., Martinez, K., Pagi, H., 2010. POLYNOMIAL TEXTURE MAPPING AND RELATED 

IMAGING TECHNOLOGIES OR THE RECORDING, ANALYSIS AND PRESENTATION OF 

ARCHAEOLOGICAL MATERIALS, in: Mills, J.P., Barber, D.M., Miller, P.E., Newton, I. (Eds.), Proceedings 

of the ISPRS Commission V Mid-Term Symposium 'Close Range Image Measurement Techniques'. 

International Society of Photogrammetry and Remote Sensing, Newcastle upon Tyne, United Kingdom, pp. 218- 

223. 

Egels, Y., Kasser, M., 2002. Digital Photogrammetry. Taylor & Francis Inc., London, UK, New York, USA; 

Canada. 

Fassi, F., Achille, C., Fregonese, L., Monti, C., 2010. MULTIPLE DATA SOURCE FOR SURVEY AND 

MODELLING OF VERY COMPLEX ARCHITECTURE, in: Mills, J.P., Barber, D.M., Miller, P.E., Newton, I. 

(Eds.), Proceedings of the ISPRS Commission V Mid-Term Symposium 'Close Range Image Measurement 

Techniques'. International Society of Photogrammetry and Remote Sensing, Newcastle upon Tyne, United 

Kingdom, pp. 234-239. 

Floth, M., Breuer, M., 2010. AN OPTICAL THREE-DIMENSIONAL MEASURING TECHNIQUE FOR A 

DETAILED NON-CONTACT DATA ACQUISITION OF OBJECT SURFACES IN THE FIELDS OF 

CULTURAL HERITAGE, ARCHEOLOGY AND THE CARE AND PRESERVATION OF HISTORIC 

MONUMENTS, in: Mills, J.P., Barber, D.M., Miller, P.E., Newton, I. (Eds.), Proceedings of the ISPRS 

Commission V Mid-Term Symposium 'Close Range Image Measurement Techniques'. International Society of 

Photogrammetry and Remote Sensing, Newcastle upon Tyne, United Kingdom, pp. 240-244. 

Fraser, C.S., Hanley, H.B., 2004. DEVELOPMENTS IN CLOSE-RANGE PHOTOGRAMMETRY FOR 3D 

MODELLING: THE iWitness EXAMPLE, in: Gruen, A., Murai, S., Fuse, T., Remondino, F. (Eds.), 

International Workshop on "Processing and Visualization using High-Resolution Images". INTERNATIONAL 

ARCHIVES OF PHOTOGRAMMETRY, REMOTE SENSING AND SPATIAL INFORMATION SCIENCES, 

Pitsanulok, Thailand, pp. 1-4. 

Fryer, J., Mitchell, H., Chandler, J., 2007. Applications of 3D Measurement from Images. Whittles Publishing, 

Caithness, Scotland, UK. 

68

REFERENCES 

Gruen, A., Huang, S.T., 2001. Calibration and Orientation of Cameras in Computer Vision. Springer, Verlag, 

Berlin, Heidelberg, Germany. 

Grussenmeyer, P., Landes, T., Voegtle, T., Ringle, K., COMPARISON METHODS OF TERRESTRIAL 

LASER SCANNING, PHOTOGRAMMETRY AND TACHEOMETRY DATA FOR RECORDING OF 

CULTURAL HERITAGE BUILDINGS. International Society of Photogrammetry and Remote Sensing, pp. 

213-218. (http://www.isprs.org/proceedings/XXXVII/congress/5_pdf/38.pdf) 

Hanke, K., Grussenmeyer, P., 2002. ARCHITECTURAL PHOTOGRAMMETRY: Basic theory, Procedures, 

Tools. ISPRS Commission 5 tutorial, Corfu. 

Hess, M., Robson, S., 2010. 3D Colour Imaging For Cultural Heritage Artefacts, in: Mills, J.P., Barber, D.M., 

Miller, P.E., Newton, I. (Eds.), Proceedings of the ISPRS Commission V Mid-Term Symposium 'Close Range 

Image Measurement Techniques'. International Society of Photogrammetry and Remote Sensing, Newcastle 

upon Tyne, United Kingdom, pp. 288-292. 

Jędrzejek, M., Łącka, M., Wykorzystanie wzorców świetlnych i metod fotogrametrycznych do pozycjonowania 

ciała ludzkiego (PiCalib), WGGiIŚ. Akademia Górniczo-Hutnicza, Kraków. (http://galaxy.uci.agh.edu.pl/~zfiit/) 

Kazanaa, E., 2010. TOPCON‟S PI-3000 IN THE INVENTORY OF DATA RELATING TO SCULPTURAL 

AND PORTABLE ARTIFACTS, in: Mills, J.P., Barber, D.M., Miller, P.E., Newton, I. (Eds.), Proceedings of 

the ISPRS Commission V Mid-Term Symposium 'Close Range Image Measurement Techniques'. International 

Society of Photogrammetry and Remote Sensing, Newcastle upon Tyne, United Kingdom, pp. 322-324. 

Kimpton, G.R., Horne, M., Heslop, D., 2010. TERRESTRIAL LASER SCANNING AND 3D IMAGING: 

HERITAGE CASE STUDY – THE BLACK GATE, NEWCASTLE UPON TYNE, in: Mills, J.P., Barber, D.M., 

Miller, P.E., Newton, I. (Eds.), Proceedings of the ISPRS Commission V Mid-Term Symposium 'Close Range 

Image Measurement Techniques'. International Society of Photogrammetry and Remote Sensing, Newcastle 

upon Tyne, United Kingdom, pp. 325-330. 

Kochi, N., Ito, T., Noma, T., Otani, H., Nishimura, S., Ito, J., PC-BASED 3D IMAGE MEASURING STATION 

WITH DIGITAL CAMERA AN EXAMPLE OF ITS ACTUAL APPLICATION ON A HISTORICAL RUIN. 

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences; 

Commission V XXXIV, Part 5/W12, 195-199. (http://www.terrageomatics.com/pdfs/PI- 

3000%20ISPRS%20Paper%20-%20Historical%20Ruin.pdf) 

Kraus, K., 2007. Photogrammetry: Geometry from Images and Laser Scans, 2 ed. Walter de Gruyter GmbH & 

Co. KG., Berlin, Germany. 

Letellier, R., Schmid, W., LeBlanc, F., Eppich, R., Chabbi, A., Recording, Documentation, and Information 

Management for the Conservation of Heritage Places. The Getty Conversation Institute. 

(http://www.getty.edu/conservation/publications/pdf_publications/guiding_principles.pdf) 

Luhmann, T., Robson, S., Kyle, S., Harley, I., 2006. Close Range Photogrammetry: Principles, Techniques and 

Aplications. Whittles Publishing, Caithness, Scotland, UK. 

Marshall, G.F., 2004. Handbook of Optical and Laser Scanning. Marcel Dekker, Inc, New York, USA; Basel, 

Switzerland. 

McCurdy, P.G., Woodward, L.A., Davidson, J.I., Wilson, R.M., Ask, R.E., Manual of Photogrammetry. Pitman 

Publishing Corporation, New York, Chicago, USA. 

Nex, F., Rinaudo, F., 2010. PHOTOGRAMMETRIC AND LIDAR INTEGRATION FOR THE CULTURAL 

HERITAGE METRIC SURVEYS, in: Mills, J.P., Barber, D.M., Miller, P.E., Newton, I. (Eds.), Proceedings of 

the ISPRS Commission V Mid-Term Symposium 'Close Range Image Measurement Techniques'. International 

Society of Photogrammetry and Remote Sensing, Newcastle upon Tyne, United Kingdom, pp. 490-495. 

Pawlak, A., Pulchny, K., 2009. Zastosowanie cyfrowych aparatów fotograficznych do fotogrametrycznego 

pomiaru wybranych części ciała ludzkiego / The application of digital cameras to photogrammetric measurement 

of chosen parts of human body., WGGiIŚ. Akademia Górniczo-Hutnicza, Kraków, p. 133. 

69

REFERENCES 

Prokos, A., Kalisperakis, I., Karras, G., 2011. AUTOMATIC POINT CLOUD GENERATION AND 

REGISTRATION WITH A STEREOVISION SLIT-SCANNER, in: Remondino, F., El-Hakim, S. (Eds.), 

Proceedings of the 4th ISPRS International Workshop 3D-ARCH; "3D Virtual Reconstruction and Visualization 

of Complex Architectures". International Society of Photogrammetry and Remote Sensing, Trento, Italy pp. 1-6. 

Schewe, H., Holl, J., Gründig, L., LIMEZ - Photogrammetric Measurement of Railroad Clearance Obstacles. 1- 

7. (http://www.technet-gmbh.de/fileadmin/Photogrammetrie/Publikationen/Limez-english.pdf) 

Schewe, H., Ifert, F., 2000. SOFT TISSUE ANALYSIS AND CAST MEASUREMENT IN ORTHODONTICS 

USING DIGITAL PHOTOGRAMMETRY, in: Chikatsu, H., Heuvel, F.v.d. (Eds.), Invited and Presented Papers 

of the XIXth Congress; Technical Commission V. International Society of Photogrammetry and Remote 

Sensing, Amsterdam, The Netherlands, pp. 699-706. 

Stathopouloua, E.K., Valanisa, A., Lermab, J.L., Georgopoulosa, A., 2011. HIGH AND LOW RESOLUTION 

TEXTURED MODELS OF COMPLEX ARCHITECTURAL SURFACES, in: Remondino, F., El-Hakim, S. 

(Eds.), Proceedings of the 4th ISPRS International Workshop 3D-ARCH: "3D Virtual Reconstruction and 

Visualization of Complex Architectures". International Society of Photogrammetry and Remote Sensing, Trento, 

Italy, pp. 1-5. 

Tucci, G., Cini, D., Nobile, A., 2011. EFFECTIVE 3D DIGITIZATION OF ARCHAEOLOGICAL 

ARTIFACTS FOR INTERACTIVE VIRTUAL MUSEUM, in: Remondino, F., El-Hakim, S. (Eds.), Proceedings 

of the 4th ISPRS International Workshop 3D-ARCH: "3D Virtual Reconstruction and Visualization of Complex 

Architectures". International Society of Photogrammetry and Remote Sensing, Trento, Italy, pp. 1-8. 

Visnovcova, J., Gruen, A., Zhang, L., 2001. IMAGE-BASED OBJECT RECONSTRUCTION AND 

VISUALIZATION FOR INVENTORY OF CULTURAL HERITAGE, Proceedings of EVA 2001 Conference - 

Electronic Imaging and Visual Arts, Florence, Italy, pp. 118-122. 

Vosselman, G., Maas, H.-G., 2010. Airborne and Terrestrial Laser Scanning. Whittles Publishing, Caithness, 


Wojtas, A.M., 2010. OFF-THE-SHELF CLOSE-RANGE PHOTOGRAMMETRIC SOFTWARE FOR 

CULTURAL HERITAGE DOCUMENTATION AT STONEHENGE, in: Mills, J.P., Barber, D.M., Miller, P.E., 




Artec, G., 2011. Artec 3D Scanners 

http://www.artec3d.com/. 

Autodesk, 2011. Autodesk Labs Utilities - Exploring new approaches to design technology - Project Photofly 2.0 

Photo Scene editor 

http://labs.autodesk.com/utilities/photo_scene_editor/. 

Canon, 2011. Canon Global 

http://www.canon.com/. 

Geomagic, 2011. Geomagic reverse engineering and 3D inspection software - "The magic of making it simple" 

http://www.geomagic.com/. 

Leksikon, S.N., Brochmann, O., Tschudi-Madsen, S., Storsletten, O., 2009. Nidarosdomen 

http://snl.no/Nidarosdomen. 

Leksikon, S.N., Dybdahl, A., Pål Bårdsson – utdypning (NBL-artikkel) 

http://snl.no/.nbl_biografi/Pål_Bårdsson/utdypning. 

Metrology, E., Artec 3D Scanner from Exact Metrology - Effortless 3D Scanning 

http://www.exact3dscanner.com/. 

Minolta, K., GmbH, B.S.E., 2011. Konica Minolta Europe - The essentials of imaging 

70

http://www.konicaminolta.eu/. 

Nidaros, D., Nidarosdomen & Erkebispegården 

http://www.nidarosdomen.no/nb-NO/. 

REFERENCES 

Organisasjon, D.K.K., Martinsen, O., 1996. Archbishop Pål (1333-1346) 

http://www.katolsk.no/organisasjon/mn/erkebiskoper/15. 

PhotoModeler, 2011. PhotoModeler - Measuring & Modeling the Real World - accurate and affordable 3D 

photogrammetry measurement and scanning 

http://www.photomodeler.com/. 

Studios, I., 3D Laser Scanning Services, A Division of Impact Studios LLC 

http://www.impactstudiostv.com/. 

TerraDat, TerraGeomatics, Topcon, I.P., Topcon ImageMaster Photo - 3D photogrammetry survey software 

http://www.terrageomatics.com/. 

Topcon, 2009. Topcon Positioning System, Inc 

http://www.topconpositioning.com/. 

Topcon, 2011. Topcon Europe Positioning B. V. 

http://www.topcon-positioning.eu/. 

Topcon, I., 2008. Topcon ImageMaster - 3D Measurement & Photogrammetry software 

http://imagemaster3d.com/. 

71

APPENDIXES 

APPENDIXES 

A. 1 Specification of Canon Camera EOS-1Ds 

72

APPENDIXES 

73

APPENDIXES 

74

APPENDIXES 

75

APPENDIXES 

A. 2 Report - results of camera calibration using PhotoModeler Scanner software 

Status Report Tree 

Project Name: Camera calibration Canon 28mm.pmr 

Problems and Suggestions (0) 

Project Problems (0) 

Problems related to most recent processing (0) 

Information from most recent processing 

Last Processing Attempt: Tue Jun 07 12:50:00 2011 

PhotoModeler Version: 6.4.0.821 - final, full 

Status: successful 

Processing Options 

Orientation: off 

Global Optimization: on 

Calibration: on (full calibration) 

Constraints: off 

Total Error 

Number of Processing Iterations: 2 

Number of Processing Stages: 2 

First Error: 0.847 

Last Error: 0.847 

Precisions / Standard Deviations 

Camera Calibration Standard Deviations 

Camera1: Canon EOS-1DS [28.00 ok] 

Focal Length 

Value: 29.361075 mm 

Deviation: Focal: 9.7e-004 mm 

Xp - principle point x 

Value: 18.020201 mm 

Deviation: Xp: 0.001 mm 

Yp - principle point y 

Value: 11.789349 mm 

Deviation: Yp: 0.001 mm 

Fw - format width 

Value: 35.761454 mm 

Deviation: Fw: 6.7e-004 mm 

Fh - format height 

Value: 23.799800 mm 

K1 - radial distortion 1 

Value: 1.419e-004 

Deviation: K1: 1.4e-007 


Value: -1.709e-007 

Deviation: K2: 3.3e-010 


Value: 0.000e+000 

P1 - decentering distortion 1 

Value: -6.230e-006 

Deviation: P1: 4.1e-007 

P2 - decentering distortion 2 

Value: -1.368e-005 

Deviation: P2: 4.2e-007 

76

Quality 

APPENDIXES 

Photographs 

Total Number: 12 

Bad Photos: 0 

Weak Photos: 0 

OK Photos: 12 

Number Oriented: 12 

Number with inverse camera flags set: 0 

Cameras 

Camera1: Canon EOS-1DS [28.00 ok] 

Calibration: yes 

Number of photos using camera: 12 

Average Photo Point Coverage: 85% 

Photo Coverage 

Number of referenced points outside of the Camera's calibrated 

coverage: 0 

Point Marking Residuals 

Overall RMS: 0.108 pixels 

Maximum: 0.463 pixels 

Point 2 on Photo 11 

Minimum: 0.096 pixels 

Point 67 on Photo 9 

Maximum RMS: 0.317 pixels 

Point 140 

Minimum RMS: 0.054 pixels 

Point 67 

Point Tightness 

Maximum: 0.00056 m 

Point 140 

Minimum: 8.6e-005 m 

Point 94 

Point Precisions 

Overall RMS Vector Length: 3.73e-005 m 

Maximum Vector Length: 4.04e-005 m 

Point 141 

Minimum Vector Length: 3.63e-005 m 

Point 101 

Maximum X: 2e-005 m 

Maximum Y: 1.98e-005 m 

Maximum Z: 2.9e-005 m 

Minimum X: 1.63e-005 m 

Minimum Y: 1.64e-005 m 

Minimum Z: 2.75e-005 m 

77

APPENDIXES 

A. 3 Comparison on photogrammetric software used in the project including system requirements, import/export files, main features camera 

calibration and modelling manipulation tools 

Application PhotoModeler Scanner V 6. Topcon ImageMaster V 2.0 (Trial – 30 days) Autodesk Project 

Photofly 2.0 

System requirements 

Operating 

System 

Windows XP; 

Windows Vista; 

Windows 7; 

Windows 98, Me, NT, 2000 also, but there 

might be video and interface driver problems; 

64 bit version runs in compability mode; 

software is 32 bit and cannot take full advantage 

of the 64 bit operating system; 

Can be installed on a Intel – based Mac running 

Windows as well 

Main features 

Import Image: 

JPG, TIF, BMP, PCX, TGA, PNG, PCT, PSD, 

PPM, MAC, IFF, CAL, PCD, SGI, RGB, JP2, 

JPX, HDP, WDP 

3D file: 

DXF, OBJ, 3D Studio, Raw text file 

Export 3DS, 3DM, DXF, FBX, IGS, KMZ, MA, MS, 

OBJ, RAW, STL, WRL; 

Mesh – specific formats: 

BYU, FACET, IV, PLY, STL, TXT 

Animation: 

GIF, AVI 

Ortho – photo: 

JPG, TIF, BMP, PCX, TGA, PNG, PSD, IFF, 

CAL, SGI, RGB 

Table: 

TXT, CSV 

Main features Modelling tools (modelling every type of 

surface, shapes etc., DSM creation) 

Coded targets: automate the setup – initial 

marking and referencing 

Photograph handling: any number of 

Windows 2000; 

Windows XP; 

Windows VISTA; 

Windows 7 

CSV (scan points, GPS control, total stations, etc.,), DXF, TIN (e.g., site 

basemaps), IS scanning data, Laser scan point cloud data, Stereo JPEGS 

acquired with standard digital camera, GPT - 7000i imaging total station 

orientation data 

DXF, CSV, VRML, TIN, Ortho – Images, Point cloud data (with coloured 

RGB values) 

IS Remote Access Control 

Grid Scan, point measurement & image capture 

Stereo Imaging / Photogrammetry 

Creation of Pass (tie) Points 

78 

Windows XP SP 3 or 

higher; 

Windows 7; 

32 – bit and 64 – bit 

systems 

Image formats 

DWG, OBJ, LAS, 

IPM, RZI 

Creating near accurate 

3D models from 

photographs using the 

web,

APPENDIXES 


Photofly 2.0 

photographs, add new photographs at any time, Bundle Adjustment 

Utilizes common point 

Camera support: images from digital, film or 3D measurements from stereo images (3D monitor supported) 

and shoot digital 

video cameras, Automatic Camera Calibration 

cameras, 

determines the position of the camera when the Tools 

image was taken, Use different cameras in the Creation and modification of points and polylines 

Harnesses the power 

same project 

Automatic generation of TIN (digital surface model at pre-defined mesh) of cloud computing to 

Camera Calibrator 

TIN / DSM editing and merging 

translate photos into 

Texture extraction and ortho – photos Creation of contours and cross sections 

detailed 3D models, 

Sub-Pixel Target Marking (based on advanced Texture mapping using digital photo input 

computer vision techniques) 

Creation of ortho – images 

3D models can be 

Edge Modelling: Model linear features even Distance measurement between two points 

manipulated by design 

when distinct end points cannot be matched Area calculations 

software (AutoCAD, 

across the photographs 

Constraints: Enter known relationships into the 

Volumetric calculations and differencing 

Inventro, 123D) 

project (e.g., parallel, perpendicular, collinear, Project Settings 

Sharing through 

etc.) to fine-tune processing 

Automated camera calibration for stereo image capture 

YouTube, iPad, 

Inverse Camera: Enter a few known control Coordinate transformations & translation 

iPhone, and iPod 

points or constraints and the focal length and 

position of an unknown camera is automatically 

calculated for projects involving single or 

multiple photos 

Single Photograph Support: Use Inverse 

Camera with several known control points or 

object constraints to model from a single photo, 

This allows the use of photographs from 

historical archives, bystanders, and third parties 

for producing 3D data 

Automated Tools for Surface Models: 

Automated marking, referencing, and surfacing 

aid in high-density surface model creation 

Bundle Adjustment 

Eos' Bundle Adjustment provides camera selfcalibration 

and full error propagation. The first 

stage of our Bundle provides automated relative 

and absolute camera orientation. 

Touch 

79

APPENDIXES 


Photofly 2.0 

Model edition/manipulation tools 

Cleaning the 

model 

Smoothing 

algorithms (point 

cloud/mesh) 

Reducing 

algorithms (point 

cloud/mesh) 

Clean outliers – remove points and small point 

clusters from the mesh that are separated from 

the main mesh and are probably noise 

Clear redundancy – remove duplicate points 

that are close to each other within the mesh 

Smooth points – adjust the points in the mesh to 

remove small bumps and imperfections 

Decimate triangles – reduce the number of 

triangles while retaining the overall shape 

Smooth triangles – adjust the triangles in the 

mesh to remove small bumps and imperfections 

Point decimation – reduce the number of points 

while retaining the shape of the point cloud 

Select – delete Select – delete 

TIN Filtering: 

� Median 

sorts the elevation around the designated point by ascending order, 

determines the median value, then replaces the elevation with the median 

value, With this filter, outlying, noise – line points can be removed, 

Another feature is that some uneven places can be retained, In order to 

increase the precision of each point it‟s necessary to narrow the 

measurement interval and measure many points, 

� Mean 

determines the average of the elevations around the designated point and 

then replaces those elevations with that average value, It can be used to 

make an entire surface smooth, In order to increase the precision of each 

point, it is necessary to narrow the measurement interval and measure 

many points 

n/a 

Triangulation Triangulation – triangulate a point cloud to 

form a surface 

n/a 

Filling holes Fill Holes – fill enclosed areas that were not 

triangulated due to missing point data 

n/a 

Texture mapping n/a Texture mapping – function for mapping texture (an image) to a selected 

surface (TIN) on the model or registration screen or on the stereo screen 

Offset n/a Offset elevations – offsetting the elevations (Z coordinates) of selected 

TIN vertices 

Reversed n/a Reversed Triangles – reversing the front and back (normal vector 

triangles 

orientation of the triangle selected 

Clipping n/a Clipping – clipping area 

80 

All steps in one set – 

computed, made and 

sent by server 

Mesh quality – 

Mobile, Standard, 

Maximum

APPENDIXES 

A. 4 Comparison of 3D digitizers: main features, specification: used methods, light, range, resolution, accuracy, etc. 

Model Konica Minolta VI-910 Artec MHT 3D Scanner Artec S 3D Scanner 

Measurement method Triangulation light block method Triangulation light block Triangulation light 

method 

block method 

Autofocus Image surface AF (contrast method); active AF Yes Yes 

Light – receiving lenses (exchangeable) TELE: Focal distance f = 25 mm 

MIDDLE: Focal distance f = 14 mm 

WIDE: Focal distance f = 8 mm 

No info No info 

Ability to capture texture Yes Yes No 

Scan range (depth of field) / working 

distance 

0,6 to 2,5 m (2m for WIDE lens) 0,4 – 1 m 0,15 – 0,25 m 

Optimal 3D measurement range 0,6 to 1,2m Whole range Whole range 

Light source Laser Flash bulb (no laser) Flash bulb (no laser) 

Laser class Class 2 (IEC60825-1), Class (FDA) n/a n/a 

Laser scan method Galvanometer – driven rotating mirror Light pattern Light pattern 

X-direction input range (varies with 111 to 463 mm (TELE), 

148 to 371 mm 56 to 93 mm 

distance) / linear field of view 

198 to 823 mm (MIDDLE), 

359 to 1196 mm (WIDE) 

Y-direction input range (varies with 83 to 347 mm (TELE), 

214 to 536 mm 80 to 134 mm 

distance) 


269 to 897 mm (WIDE) 

Z-direction input range (varies with 40 to 500 mm (TELE), 

No info No info 

distance) 


110 to 750 mm (WIDE) 

Angular field of view, HxW No info 30x21° 30x21° 

3D resolution No info Up to 0,5 mm Up to 0,2 mm 

Accuracy / 3D point accuracy X: ±0,22 mm, Y: ±0,16 mm, Z: ±0,10 mm to the Z reference plane 

(Conditions: TELE/ FINE mode, Konica Minolta‟s standard) 

Up to 0,1 mm Up to 0,05 mm 

3D accuracy over distance No info Up to 0,15% over 100 cm Up to 0,15% over 100 

cm 

Exposure time n/a 0,0002 s 0,0002 s 

Video frame rate n/a Up to 15 fps Up to 15 fps 

Input time / Data acquisition speed 0,3 s (FAST mode) or 

1,5 s (FINE mode) 

Up to 500 000 points/s Up to 500 000 points/s 

Ambient lighting condition 500 lx or less No info No info 

Imaging element 3D data: 1/3 inch frame – transfer CCD (340 000 pixels) 

Colour data: 3D data is shared (colour separation by rotary filter) 

No info n/a 

81

APPENDIXES 

Model Konica Minolta VI-910 Artec MHT 3D Scanner Artec S 3D Scanner 

Number of output pixels / texture 3D data: 307 000 (FINE mode), 76 800 (FAST mode) 

1,3 mp 

n/a 

resolution; colours 

Colour data: 640 x 480 x 24 bits colour depth 

24 bpp 

n/a 

Data file size Total 3D data and colour data capacity: 

Depending on amount of Depending on amount 

1,6 MB (FAST mode) per data, 

3,6 MB (FINE mode) per data 

frames and texture 

of frames 

Dimensions (W x H x D) 213 x 413 x 271mm (8- 3/8 x 16 – ¼ x 10-11/16 in,) 260 x 180 x 187 mm 80 x 125 x 195 mm 

Weight Approximately 11 kg (25 lbs) 1,6 kg 1,6 kg 

Processing capacity No info 40 000 000 triangles / 1 GB 40 000 000 triangles / 1 

RAM 

GB RAM 

82

APPENDIXES 

A. 5 Comparison of software from scanning systems; main features, system requirements, model manipulation tools. 

Application Konica Minolta Polygon Editing Tool V2.20 Artec 3D Scanner 

System requirements: 

OS / Operating 

System 

Main features 

Readable formats / 

Scan data formats 

Output formats / 

Exporting 

Windows 2000 Professional SP4, 

XP Professional SP2 (x64 Edition not supported) 

83 

Windows XP 32, 

Vista 32 / 64, 

7 32 / 64 

CAM, WD, SCN, CDM, CDK 

General format: STL 

Artec formats 

Konica Minolta formats & STL, DXF, OBJ, ASCII points, VRML STL, PLY, WRL, OBJ, PTX, CSV, ASC, AOP 

Multi core processing No Yes 

Camera remote 

operation 

Main Functions / 

features 

Measurement, 

measurement reference distance setting, 

number of scans setting, 

laser power setting, 

high – quality setting, 

filter setting, etc., 

Scanning, 

Data alignment, 

data merging, 

smoothing, 

data reduction, 

polygon check, 

hole filling with data interpolation, 

texture blending 

measuring tools 

Display modes: 

Wireframe, 

shading, 

texture mapping 

Light settings for texture 

Working distance settings 

Number of frames settings 

Scanning, 

multicapturing, 

scan alignment, 

global optimization, 

model fusion, 

smoothing, 

simplify, 

hole filling with data interpolation, 

repair tool, 

texture mapping, 

measuring tools 


Points, 

Wireframe 

Shading 

Lighting, etc. 

Texture

APPENDIXES 


Model manipulation tools 

Aligning point 3 corresponding point need for manual initial registration; 

3 corresponding point need for manual initial 

cloud/mesh 

Any number of scans can be aligned with fine registration 

registration; 

Any number of scans can be aligned with fine 

registration and then global registration, which 

improves the results 

Merging point Scans seems to be slightly moved, again and some data seem to be lost – more holes “Fusion” tool, which seems to move a bit scans and 

cloud/mesh 

smooth the model, sometimes resulting with more holes 

Cleaning the model Select - Delete Eraser brush – select and remove unwanted objects 

Singletons – removing occasionally encounter outliers – 

small areas or fragments untied to the model; 

� Filter by threshold 

all scene objects smaller than the specified size (number 

of polygons) determined by the threshold parameter will 

be removed; 

� Leave biggest objects 

Smoothing algorithm Smooth: 

leaves only the biggest objects in each frame 

Smooth – algorithm which allows smoothing out noise, 

(point cloud/mesh) � Element – makes selected elements smooth as well as to regularize surface outliers on the 3D model and makes it generally 

points density; 

smoother 

� Points – makes boundary of the points selected in the currently displayed 

element smooth as well as regularize surface points density 

Smooth brush – select and smooth small parts 

Reducing algorithm Subsample 

Simplify – optimization algorithm operation 

(point cloud/mesh) � Uniformly – Element/Points – reduces the data of the points of the selected 

element so that surface points density becomes uniform 

� Adaptively – Element/Points – reduces the data of the points of the selected 

element so that surface points density in simple-shaped areas is lower than in 

complicated-shaped areas 

Filling holes 

Modify – Element / Points – rebuilds the selected element / points t by deleting small 

polygons 

Fill Holes: 

Fill Holes – or 

� Manually (by manually selecting holes) 

Filling Holes using separate special tool Holes 

� Automatically (create polygon data automatically for the holes However, 

some complicated holes may not be filled 

Repair Check Polygons – checking for illegal polygons among those compromising the 

selected element 

Repair (mesh) 

84

APPENDIXES 


Adding points Subdivision – Element / Points– rebuilds the selected element / points by dividing 

large polygons 

n/a 

Triangulate Triangulate – Elements/ Polygon – dividing polygons of the selected element(s) / No info 

points into triangles, 

Triangulated point cloud is set from view menu 

Texture mapping Texture Blending – making the edges of colour image of registrated element smooth Texture mapping – applying texture onto the 3D model 

from photos 

85

APPENDIXES 

A. 6 Geomagic Qualify: main features, import/export files, system requirements and main manipulation tools used in the project 

Application Geomagic Qualify V 12 

System requirements: 

OS / Operating System Windows 7 (32 and 64 bit); 

Windows Vista SP1 (32 and 64 bit); 

Windows XP SP3 (32 and 64 bit) 

CPU / Processor Intel compatible 2 GHz / Dual or Quad core 2 GHz CPU‟s recommended 

Main features 

Readable formats / Scan 

data formats (input) 

Supports all 3D digitizers, cameras and scanners in XYZ / ASCII format: 

3PI, AC, ASC, BIN, SWL, BRE, BTX, CDK, CDM, RGV, RVM, VVD, COP, CWK, DBT, FLS, G3D, SURF – GOM, GPD, GTI, HYM, 

ICV, MET, MTN, NET, OPD, OPT, PIX, PMJ/ X, PTX, SAB2, SCN, MGP, SCN, STB, XYZ, XYZN, ZFS 

Output formats / Exporting Polygon Import / Export: 

3DS, DXF, IGS, LWO, NAS, OBJ, PLY, STL, VRML, WRP 

CAD Import / Export: 

IGES, STEP 203/214, VDA, PRO / ENGINEER (.PRT), PARASOLID (.X_T* and .X_B*), SAT 

Reports: 

3D PDF, HTML, Microsoft Word, PPT, Excel formats, CSV, Unicode data, SPC 

Available translators CAIA V4 & V5, NX, Solidworks 

Languages Chinese, English, French, German, Italian, Japanese, Russian, Czech, Brazilian Portuguese, Spanish 

Main Functions / features Scan data (Collect point and polygon data from all major 3D scanners, digitizers and hard-probing devices) 

Aligning scans (Weighted RPS alignment) 

Data merging, 

Smoothing, 

Data reduction, 

hole filling with data interpolation, defining exact shapes, 

Mesh check, 

Comparing (illustration of deviations, reports, etc.) 

Evaluate (Creation of cross-sections, detect and inspect geometrical features, calculate size, analyse fit, compare features, measuring 

distances, angles) 

Reporting, 

Automate: 

� Automate the inspection process from alignment to the generation of inspection reports 

� Record steps in the inspection process to inspect multiple parts automatically 

� Define macros for automating repetitive tasks 

Geomagic Blade Module (Optional) 

Texture mapping available in Geomagic Wrap or Studio 

86

APPENDIXES 



Different colour (or texture) 

Reflectiveness 

Light sources 

Light type 

Transparency of the model 

And many more… 

Model manipulation tools 

Aligning point cloud/ mesh From full automatic to manual, needs at least 3 corresponding points for initial registration; global registration with any amount of scans; 

also “Overlap reduction” tool which improve the results and align the scans better 

Merging point cloud / mesh Merging all scan together; all points without any data lost or adding any points 

Cleaning the model Select – Delete points / triangles 

Crop Points – Deletes all points from an object except selected points 

Select: 

� Outliers - Select points that are at least a given distance from most others 

Smoothing algorithm (point 

cloud / mesh) 

Reducing algorithm (point 

cloud / mesh) 

� Disconnected Components – evaluates the proximity of points and select groups of points that are distant from other group 

Smooth: 

� Reduce Noise Points – Compensates for scanner error (noise) by moving points to statistically correct locations, 

� Reduce Noise (mesh) – compensates for noise such as scanner error by moving points to statistically correct locations, Noise can 

cause sharp edges to become dull or smooth curves to become rough 

� Remove Spikes – detects and flattens single – point spikes on a polygon mesh 

Sample: 

� Uniform – Reduces the number of points on flat surfaces uniformly, but reduces the number of points on curved surfaces to a 

specified density 

� Curvature – Reduces the number of points in flat regions but preserves points in high – curvature areas to maintain detail 

� Grid – Reduces the number of pints in an Unordered Point object by creating an evenly spaced set of points, regardless of curvature 

and original density 

� Random – Removes a percentage of points randomly from an Unordered Points object 

� Decimate – Reduces the number of triangles without compromising surface detail or colour 

Filling holes Fill Holes – Inserts ordered points into voids on the surface of an unordered point object 

Fill All – fills all selected holes on the active Polygon object 

Fill Single – fills the hole or holes that are chosen as click one at a time in the Graphics Area, according to the setting in the Fill Holes ribbon 

group; Ribbon Group: Specifies that the new mesh must match the curvature of the surrounding mesh: 

� Curvature; 

� Tangent – more tapering than Curvature; 

� Flat – new mesh is generally flat, 

� Complete – specifies that an entire opening will be filled; 

87

APPENDIXES 


� Partial – Specifies that a portion of a hole will be filled, 

� Bridge – Specifies that a bridge across a hole will be built, thus dividing it into separately fillable holes, This may be used to divide 

a complex hole into smaller ones that can be filled more correctly, 

Repair Normals – Commands that manipulate normal information on unordered point objects: 

� Repair – Manipulates, Flips and/or removes normal information on an unordered point object 

� Remove – Deactivates the shading of Point objects 

Scan lines – A set of commands that repair scan lines (which are created only by some scanning devices): 

� Interpolate – optimizes scanlines in preparation for Wrap / 

� Order – convents unordered scanline data to ordered data (applicable to Point objects captured with a line scanner) 

Mesh: 

� Mesh Doctor (Automatically repair imperfections in a polygon mesh), Looking for: 

o Non-Manifold Edges 

o Self-Intersections 

o Highly Creased Edges 

o Spikes 

o Small Components 

o Small Tunnels 

o Small Holes 

Also possible, to: 

o Clean 

o Defeature 

o Fill Holes 

o Make Manifold 

� Make Manifold - Set of commands that delete non-manifold triangles; Manifold triangle is one that is connected the others on all 

three sides, or on two sides if it lies on an edge) 

� Open - Deletes non-manifold triangles from an otherwise open manifold objects 

� Closed- from closed objects (volume enclosing) – On an open manifold objects, all triangles would be considered nonmanifold 

and the entire object would be deleted 

� Trim – Superimposes a plane on the object and removes all triangles on one side of that plane, or creates an artificial boundary line 

at the intersection: 

o Plane -Superimposes a plane on the object and removes all triangles on one side of that plane, or creates an artificial 

boundary line at the intersection 

o Sheet – cuts 3 dimensional chunk from a polygon object by slicing it with a 2 dimensional curve) 

� Repair Tool : 

o Repair Normals – repairs normal directions of polygons whose “front” and “back” sides are confused – a problem caused 

by wrapping a Noisy point object 

o Flip normals – reverses the normal direction of a Polygon mesh – flips the “front” and “back” sides of the entire mesh) 

88

APPENDIXES 


Adding points Add points – adds individual points to a plane in an unordered point object 

Offset Offset Points – Moves unordered points by a user – specified distance in their normal directions 

Offset – applies a uniform offset and thus makes an object larger or smaller 

Triangulate Wrap – Converts a Point object into an polygon object by converting the point cloud to a mesh – triangulation to TIN 

Texture mapping Texturing available in Geomagic Wrap or Studio, in Qualify texture is available only from default pallet 

Other Compensate Deviations – creates a polygon object that will serve as input to a rapid prototyping machine and which compensates for a 

consistent flaw in that machine 

And more… 

Akca, D., Remondino, F., Novák, D., Hanusch, T., Schrotter, G., Gruen, A., Recording and modeling of cultural heritage objects with coded structured light 

projection systems, pp. 1-7. 

Alyilmaza, C., Alyilmaza, S., Yakarb, M., 2010. MEASUREMENT OF PETROGLYHPS (ROCK OF ARTS) OF QOBUSTAN WITH CLOSE RANGE PHOTOGRAMMETRY, 

in: Mills, J.P., Barber, D.M., Miller, P.E., Newton, I. (Eds.), Proceedings of the ISPRS Commission V Mid-Term Symposium 'Close Range Image Measurement 

Techniques'. International Society of Photogrammetry and Remote Sensing, Newcastle upon Tyne, United Kingdom, pp. 29-32. 

Artec, G., 2011. Artec 3D Scanners 

http://www.artec3d.com/. 

Autodesk, 2011. Autodesk Labs Utilities - Exploring new approaches to design technology - Project Photofly 2.0 Photo Scene editor 

http://labs.autodesk.com/utilities/photo_scene_editor/. 

Bache, S.N., 2003. Scanning av skulptur på Nidarosdomen. Vinn Design, Oslo, Trondheim, pp. 1-4. 

Balestrinia, E.F.d., Guerra, F., 2011. NEW INSTRUMENTS FOR SURVEY: ON LINE SOFTWARES FOR 3D RECONSTRUCTION FROM IMAGES; ISPRS Commission V - 

WG 4; Poster Session, in: Remondino, F., El-Hakim, S. (Eds.), Proceedings of the 4th ISPRS International Workshop 3D-ARCH: "3D Virtual Reconstruction and 

Visualization of Complex Architectures". International Society of Photogrammetry and Remote Sensing, Trento, Italy, pp. 1-8. 

Barba, S., Fiorillo, F., Coder, P.O., D’Auria, S., Feo, E.D., 2011. AN APPLICATION FOR CULTURAL HERITAGE IN ERASMUS PLACEMENT. SURVEYS AND 3D 

CATALOGUING ARCHAEOLOGICAL FINDS IN MÉRIDA (SPAIN), in: Remondino, F., El-Hakim, S. (Eds.), Proceedings of the 4th ISPRS International Workshop 3D- 

ARCH: "3D Virtual Reconstruction and Visualization of Complex Architectures". International Society of Photogrammetry and Remote Sensing, Trento, Italy, 

pp. 1-6. 

Barnett, T., Bryan, P., Chandler, J., Case study: Recording Prehistoric Rock Art; Pre-historic photogrammetry and laser scanning, Tertia Barnett 

Paul Bryan 

Jim Chandler, pp. 1-2. 

89

APPENDIXES 

Blais, F., 2004. Review of 20 Years Of Range Sensor Development. Journal of Electronic Imaging 13(1), 231-240. 

Blake, W.H., 2010. WHAT IS THE FUTURE OF METRIC HERITAGE DOCUMENTATION AND ITS SKILLS?, in: Mills, J.P., Barber, D.M., Miller, P.E., Newton, I. (Eds.), 

Proceedings of the ISPRS Commission V Mid-Term Symposium 'Close Range Image Measurement Techniques'. International Society of Photogrammetry and 

Remote Sensing, Newcastle upon Tyne, United Kingdom, pp. 98-102. 

Bonfanti, C., Chiabrando, F., Spanò, A., 2010. HIGH ACCURACY IMAGES AND RANGE BASED ACQUIRING FOR ARTISTIC HANDWORKS 3D-MODELS., in: Mills, 

J.P., Barber, D.M., Miller, P.E., Newton, I. (Eds.), Proceedings of the ISPRS Commission V Mid-Term Symposium 'Close Range Image Measurement 


Brutto, M.L., Spera, M.G., 2011. IMAGE-BASED AND RANGE-BASED 3D MODELLING OF ARCHAEOLOGICAL CULTURAL HERITAGE: THE TELAMON OF THE 

TEMPLE OF OLYMPIAN ZEUS IN AGRIGENTO (ITALY), in: Remondino, F., El-Hakim, S. (Eds.), Proceedings of the 4th ISPRS International Workshop 3D-ARCH: 

"3D Virtual Reconstruction and Visualization of Complex Architectures". International Society of Photogrammetry and Remote Sensing, pp. 1-8. 

Canon, 2011. Canon Global 

http://www.canon.com/. 

Chmielewski, K., Szulwic, J., Niemetryczne zdjęcia cyfrowe w fotogrametrii bliskiego zasięgu w systemie Topcon PI-2000, Sesja Jubileuszowa 60-lecia Katedry 

geodezji Politechniki Gdaoskiej, pp. 1-8. 

Deseilligny, M.P., Clery, I., 2011. APERO, AN OPEN SOURCE BUNDLE ADJUSMENT SOFTWARE FOR AUTOMATIC CALIBRATION AND ORIENTATION OF SET OF 

IMAGES., in: Remondino, F., El-Hakim, S. (Eds.), Proceedings of the 4th ISPRS International Workshop 3D-ARCH: "3D Virtual Reconstruction and Visualization 

of Complex Architectures". International Society of Photogrammetry and Remote Sensing, Trento, Italy, pp. 1-8. 

Floth, M., Breuer, M., 2010. AN OPTICAL THREE-DIMENSIONAL MEASURING TECHNIQUE FOR A DETAILED NON-CONTACT DATA ACQUISITION OF OBJECT 

SURFACES IN THE FIELDS OF CULTURAL HERITAGE, ARCHEOLOGY AND THE CARE AND PRESERVATION OF HISTORIC MONUMENTS, in: Mills, J.P., Barber, 

D.M., Miller, P.E., Newton, I. (Eds.), Proceedings of the ISPRS Commission V Mid-Term Symposium 'Close Range Image Measurement Techniques'. 

International Society of Photogrammetry and Remote Sensing, Newcastle upon Tyne, United Kingdom, pp. 240-244. 

Geomagic, 2011. Geomagic reverse engineering and 3D inspection software - "The magic of making it simple" 

http://www.geomagic.com/. 

Hess, M., Robson, S., 2010. 3D Colour Imaging For Cultural Heritage Artefacts, in: Mills, J.P., Barber, D.M., Miller, P.E., Newton, I. (Eds.), Proceedings of the 

ISPRS Commission V Mid-Term Symposium 'Close Range Image Measurement Techniques'. International Society of Photogrammetry and Remote Sensing, 

Newcastle upon Tyne, United Kingdom, pp. 288-292. 

Jędrzejek, M., Łącka, M., Wykorzystanie wzorców świetlnych i metod fotogrametrycznych do pozycjonowania ciała ludzkiego (PiCalib), WGGiIŚ. Akademia 

Górniczo-Hutnicza, Kraków. 

Kazanaa, E., 2010. TOPCON’S PI-3000 IN THE INVENTORY OF DATA RELATING TO SCULPTURAL AND PORTABLE ARTIFACTS, in: Mills, J.P., Barber, D.M., Miller, 

P.E., Newton, I. (Eds.), Proceedings of the ISPRS Commission V Mid-Term Symposium 'Close Range Image Measurement Techniques'. International Society of 

Photogrammetry and Remote Sensing, Newcastle upon Tyne, United Kingdom, pp. 322-324. 

90

APPENDIXES 

Kochi, N., Ito, T., Noma, T., Otani, H., Nishimura, S., Ito, J., PC-BASED 3D IMAGE MEASURING STATION WITH DIGITAL CAMERA AN EXAMPLE OF ITS ACTUAL 

APPLICATION ON A HISTORICAL RUIN. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences; Commission V 

XXXIV, Part 5/W12, 195-199. 

Leksikon, S.N., Brochmann, O., Tschudi-Madsen, S., Storsletten, O., 2009. Nidarosdomen 

http://snl.no/Nidarosdomen. 

Leksikon, S.N., Dybdahl, A., Pål Bårdsson – utdypning (NBL-artikkel) 

http://snl.no/.nbl_biografi/Pål_Bårdsson/utdypning. 

Luhmann, T., Robson, S., Kyle, S., Harley, I., 2006. Close Range Photogrammetry: Principles, Techniques and Aplications. Whittles Publishing, Caithness, 


Metrology, E., Artec 3D Scanner from Exact Metrology - Effortless 3D Scanning 

http://www.exact3dscanner.com/. 

Minolta, K., GmbH, B.S.E., 2011. Konica Minolta Europe - The essentials of imaging 

http://www.konicaminolta.eu/. 

Nidaros, D., Nidarosdomen & Erkebispegården 

http://www.nidarosdomen.no/nb-NO/. 

Organisasjon, D.K.K., Martinsen, O., 1996. Archbishop Pål (1333-1346) 

http://www.katolsk.no/organisasjon/mn/erkebiskoper/15. 

Pawlak, A., Pulchny, K., 2009. Zastosowanie cyfrowych aparatów fotograficznych do fotogrametrycznego pomiaru wybranych części ciała ludzkiego / The 

application of digital cameras to photogrammetric measurement of chosen parts of human body., WGGiIŚ. Akademia Górniczo-Hutnicza, Kraków, p. 133. 

PhotoModeler, 2011. PhotoModeler - Measuring & Modeling the Real World - accurate and affordable 3D photogrammetry measurement and scanning 

http://www.photomodeler.com/. 

Studios, I., 3D Laser Scanning Services, A Division of Impact Studios LLC 

http://www.impactstudiostv.com/. 

TerraDat, TerraGeomatics, Topcon, I.P., Topcon ImageMaster Photo - 3D photogrammetry survey software 

http://www.terrageomatics.com/. 

Topcon, 2009. Topcon Positioning System, Inc 

91

http://www.topconpositioning.com/. 

Topcon, 2011. Topcon Europe Positioning B. V. 

APPENDIXES 

http://www.topcon-positioning.eu/. 

Topcon, I., 2008. Topcon ImageMaster - 3D Measurement & Photogrammetry software 

http://imagemaster3d.com/. 

Tucci, G., Cini, D., Nobile, A., 2011. EFFECTIVE 3D DIGITIZATION OF ARCHAEOLOGICAL ARTIFACTS FOR INTERACTIVE VIRTUAL MUSEUM, in: Remondino, F., 

El-Hakim, S. (Eds.), Proceedings of the 4th ISPRS International Workshop 3D-ARCH: "3D Virtual Reconstruction and Visualization of Complex Architectures". 

International Society of Photogrammetry and Remote Sensing, Trento, Italy, pp. 1-8. 

Wojtas, A.M., 2010. OFF-THE-SHELF CLOSE-RANGE PHOTOGRAMMETRIC SOFTWARE FOR CULTURAL HERITAGE DOCUMENTATION AT STONEHENGE, in: 

Mills, J.P., Barber, D.M., Miller, P.E., Newton, I. (Eds.), Proceedings of the ISPRS Commission V Mid-Term Symposium 'Close Range Image Measurement 


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