To the Graduate Council: I am submitting herewith a dissertation ...

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5.5 View-dependentoverlapping......................... 855.6 Checking overlap for back-facing triangles . . . . . . . . . . . . . . . . . 855.7 Gap between surfaces after deleting overlapping triangles . . . . . . . . 865.8 Generatingasigneddistancefieldinavolumetricgrid .......... 895.9 Hole filling illustrated in a slice of volumetric grid . . . . . . . . . . . . . 926.1 Geodesicneighborhoodonawaterneckmodel............... 956.2 Fastmarchingwatershed........................... 1016.3 Segmentingaplateauarea.......................... 1047.1 Rawrangedata................................ 1077.2 Rangedataregularizationresult ...................... 1077.3 Results of median filtering, nonadaptive and adaptive regularization . . 1097.4 Surfacesmoothingofsyntheticdata .................... 1107.5 Smoothingsurfacesfromscansofawaterneck............... 1117.6 Smoothingsurfacesfromscansofacrank ................. 1127.7 Smoothing surfaces captured by the RIEGL System . . . . . . . . . . . 1137.8 Adaptivesmoothingofasurfacemesh ................... 1147.9 3Dregistrationofsyntheticrangedata................... 1177.10RegistrationofDEMdata.......................... 1187.11Matchingsurfacesofabrainmodel..................... 1197.12Matchingsurfacesofafacemodel...................... 1207.13Matchingsurfacesofamannequinface................... 121xiii
7.14 Finding corresponding points on surfaces with noise . . . . . . . . . . . 1227.15 Matching surfaces with different resolutions . . . . . . . . . . . . . . . . 1237.16ICPrefinement ................................ 1247.17 Surface reconstruction using mesh zippering . . . . . . . . . . . . . . . . 1267.18Two-viewintegrationbyimplicitsurfacefusion .............. 1277.19 Implicit surface-based reconstruction of a synthetic object . . . . . . . . 1277.20Surfacemodelingofacrankandadiskbrake ............... 1297.21 Surface modeling of a waterneck and a distributor cap . . . . . . . . . . 1307.22 Surface modeling of a racecar and a mannequin . . . . . . . . . . . . . . 1317.23 Automatic hole filling ............................ 1327.24SurfacemodelingusingtheCOLEMANscanner.............. 1337.25 Surface modeling using the RIEGL scanner . . . . . . . . . . . . . . . . 1347.26 Four indoor range images scanned by the RIEGL scanner . . . . . . . . 1357.27 Four-view reconstruction using the RIEGL scanner . . . . . . . . . . . . 1367.28Segmentationprocess............................. 1387.29Surfacesegmentationofsmallparts..................... 1397.30Surfacesegmentationofascene....................... 1407.31Manipulatingsegmentedparts........................ 1417.32Applicationofthesurfacemodelingframework .............. 143A.1 Laser range scanners based on time-of-flight . . . . . . . . . . . . . . . . 164A.2 Laser range scanners based on triangulation . . . . . . . . . . . . . . . . 167xiv
Page 1 and 2: To the Graduate Council:I am submit
Page 3 and 4: Copyright c○ Yiyong Sun, 2002All
Page 5 and 6: AcknowledgmentsFirst and foremost,
Page 7 and 8: search employs an implicit surface-
Page 9 and 10: 3.2.2 Edge Preservation for Range D
Page 11 and 12: 8.2 Future Research . . . .........
Page 13: List of Figures1.1 A framework for
Page 17 and 18: Chapter 1IntroductionThis introduct
Page 19 and 20: Range ImageSmoothingRegistrationCol
Page 21 and 22: obust to surface noise and registra
Page 23 and 24: more efficient than 2D image correl
Page 25 and 26: scending path, and region merging.L
Page 27 and 28: two-dimensional (2D) image, 2D lowp
Page 29 and 30: curvatures of points on a surface i
Page 31 and 32: smoothing on the surface mesh. Shri
Page 33 and 34: with different surface representati
Page 35 and 36: center point and every surface poin
Page 37 and 38: Table 2.1: Comparison of different
Page 39 and 40: Reconstruction from Unorganized Poi
Page 41 and 42: tional. An offset of the distance f
Page 43 and 44: surement confidence. However, in or
Page 45 and 46: triangle mesh. The triangle mesh is
Page 47 and 48: mesh segmentation based on the phys
Page 49 and 50: Rettmann et al. [70] proposed a mes
Page 51 and 52: successful smoothing for both raw r
Page 53 and 54: where lim t→0 (R/t) =0,H represen
Page 55 and 56: the range r ij is estimated instead
Page 57 and 58: y minimizing the following energy f
Page 59 and 60: tions were used:r α = r i,j+1 −
Page 61 and 62: where κ represents a parameter tha
Page 63 and 64: inequality, such asI∑I∑S i ≤
Page 65 and 66:
n ′ in iT ipqn ipw in ′ i−→
Page 67:
The singular value decomposition is
Page 70 and 71:
a limit on sharp edges. This limit
Page 72 and 73:
of the smoothing.Surface smoothing
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fingerprint are presented. Section
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erroneously includes surface patch
Page 78 and 79:
(ρ, θ)ρθT p (S)expSexp p (ρ,
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exponential map is introduced.4.2 F
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accurately than Dijkstra’s algori
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andθ = arccos ρ2 (A)+|AB| 2 −
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andy =((n × −→ pm) × n) · v
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images.4.3 Candidate Point Selectio
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(a)(b)(c)(d)Figure 4.6: Global fing
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and R ij is below a threshold. The
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If the singular-value decomposition
Page 96 and 97:
Chapter 5Surface Reconstruction fro
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Figure 5.2: Two registered and over
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Figure 5.4: Intersecting triangles.
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Figure 5.7: Gap between surfaces af
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5.2 Volume-Based Surface Integratio
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2D texture coordinate of x is set t
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ABFigure 5.9: Hole filling illustra
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are presented in Section 7.4.6.1 A
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6.3 Applying the Fast Marching Wate
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Algorithm 6.2 (Fast Marching Waters
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15: end if16: if v i.h
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6.3.2 Geodesic ErosionThis step ass
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(a)(b)(c)(d)Figure 6.3: Segmenting
Page 122 and 123:
Chapter 7Experimental ResultsThis c
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no discernible improvement. For fai
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(a)(b)(c)(d)Figure 7.4: Surface smo
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(a)(b)(c)(d)Figure 7.6: Smoothing s
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(a)(b)(c)(d)(e)(f)Figure 7.8: Adapt
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The real range images were scanned
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(a)(b)Figure 7.10: Registration of
Page 136 and 137:
(a)(b)(c)(d)(e)(f)Figure 7.12: Matc
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(a) (b) (c) (d)(e) (f) (g) (h)(i)(j
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(a)(b)ICP Registration Error (mm)21
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(a)(b)(c)(d)(e)(f)Figure 7.17: Surf
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Table 7.1: Small parts 3D reconstru
Page 146 and 147:
(a)(b)(c)(d)Figure 7.21: Surface mo
Page 148 and 149:
(a)(b)Figure 7.23: Automatic hole f
Page 150 and 151:
(a)(b)(c)(d)(e)(f)(g)(h)Figure 7.25
Page 152 and 153:
(a)(b)(c)(d)Figure 7.27: Four-view
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(a)(b)(c)(d)Figure 7.28: Segmentati
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(a)(b)(c)(d)Figure 7.30: Surface se
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Table 7.2: Performance of the fast
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surface reconstructed from the raw
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to choose a proper flowing step siz
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of interest based on the shape irre
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8.2 Future ResearchThere are many o
Page 168 and 169:
Bibliography[1] E. L. Allgower and
Page 170 and 171:
[26] G. Dziuk and J. E. Hutchinson.
Page 172 and 173:
[54] W. E. Lorensen and H. E. Cline
Page 174 and 175:
[81] M. Soucy and D. Laurendeau. A
Page 176 and 177:
[106] S. M. Yamany, A. A. Farag, an
Page 178 and 179:
Appendix ALaser Range ScannersLaser
Page 180 and 181:
(a)(b)Transmitter LensTargetDiodeLa
Page 182 and 183:
A.2 Scanners Based on Laser Triangu
Page 184 and 185:
LaserBaseline B-s0saOpticalCenter(a
Page 186 and 187:
Appendix BSimplification of theArea
Page 188:
VitaYiyong Sun was born in Beijing,
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