Abstract book (pdf) - ICPR 2010

09:20-09:40, Paper TuAT3.2
A Color Invariant based Binary Coded Structured Light Range Scanner for Shiny Objects
Benveniste, Rifat, Yeditepe Univ.
Unsalan, Cem, Yeditepe Univ.
Object range data provide valuable information in recognition and modeling applications. Therefore, it is extremely important
to reliably extract the range data from a given object. There are various range scanners based on different principles.
Among these, structured light based range scanners deserve spacial attention. In these systems, coded light stripes are projected
onto the object. Using the bending of these light stripes on the object and the triangulation principle, range information
can be obtained. Since this method is simple and fast, it is used in most industrial range scanners. Unfortunately,
these range scanners can not scan shiny objects reliably. The main reason is either highlights on the shiny object or the
ambient light in the environment. These disturb the coding by illumination. As the code is changed, the range data extracted
from it will also be disturbed. In this study, we propose a color invariant based binary coded structured light range scanner
to solve this problem. The color invariant used can eliminate the effects of highlights on the object and the ambient light
from the environment. This way, we can extract the range data of shiny objects in a robust manner. To test our method, we
developed a prototype range scanner. We provide the obtained range data of various test objects with our range scanner.
09:40-10:00, Paper TuAT3.3
Improving Shape-From-Focus by Compensating for Image Magnification Shift
Pertuz, Said|, Rovira I Virgili Univ.
Puig, Domenec, Rovira I Virgili Univ.
Garcia, Miguel Angel, Autonomous Univ. of Madrid
Images taken with different focus settings are used in shape-from-focus to reconstruct the depth map of a scene. A problem
when acquiring images with different focus settings is the shift of image features due to changes in magnification. This
paper shows that those changes affect the shape-from-focus performance and that the final reconstruction can be improved
by compensating for that shift. The proposed scheme takes into account the effects due to magnification changes between
near and far focused images and it is able to determine the depth of the scene points with higher accuracy than traditional
techniques. Experimental results of the application of the proposed method are shown.
10:00-10:20, Paper TuAT3.4
Quasi-Dense Wide Baseline Matching for Three Views
Koskenkorva, Pekka, Univ. of Oulu
Kannala, Juho, Univ. of Oulu
Brandt, Sami Sebastian, Univ. of Oulu
This paper proposes a method for computing a quasi-dense set of matching points between three views of a scene. The
method takes a sparse set of seed matches between pairs of views as input and then propagates the seeds to neighboring
regions. The proposed method is based on the best-first match propagation strategy, which is here extended from twoview
matching to the case of three views. The results show that utilizing the three-view constraint during the correspondence
growing improves the accuracy of matching and reduces the occurrence of outliers. In particular, compared with
two-view stereo, our method is more robust for repeating texture. Since the proposed approach is able to produce high
quality depth maps from only three images, it could be used in multi-view stereo systems that fuse depth maps from multiple
views.
10:20-10:40, Paper TuAT3.5
Robust Shape from Polarisation and Shading
Huynh, Cong Phuoc, Australian National Univ.
Robles-Kelly, Antonio, National ICT Australia
Hancock, Edwin, Univ. of York
In this paper, we present an approach to robust estimation of shape from single-view multi-spectral polarisation images.
The developed technique tackles the problem of recovering the azimuth angle of surface normals robust to image noise
and a low degree of polarisation. We note that the linear least-squares estimation results in a considerable phase shift from
the ground truth in the presence of noise and weak polarisation in multispectral and hyper spectral imaging. This paper
discusses the utility of robust statistics to discount the large error attributed to outliers and noise. Combining this approach
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