Geo-consistency for wide multi-camera stereo

This paper presents a new model to overcome the occlusion problems coming from wide baseline multiple camera stereo. Rather than explicitly modeling occlusions in the matching cost function, it detects occlusions in the depth map obtained from regular efficient stereo matching algorithms. Occlusions...

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Bibliographic Details
Published in2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) Vol. 1; pp. 351 - 358 vol. 1
Main Authors Drouin, M.-A., Trudeau, M., Roy, S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Cameras
Convergence
Cost function
History
Image reconstruction
Iterative algorithms
Layout
Photometry
Stereo image processing
Stereo vision
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Summary:This paper presents a new model to overcome the occlusion problems coming from wide baseline multiple camera stereo. Rather than explicitly modeling occlusions in the matching cost function, it detects occlusions in the depth map obtained from regular efficient stereo matching algorithms. Occlusions are detected as inconsistencies of the depth map by computing the visibility of the map as it is reprojected into each camera. Our approach has the particularity of not discriminating between occluders and occludees. The matching cost function is modified according to the detected occlusions by removing the offending cameras from the computation of the matching cost. The algorithm gradually modifies the matching cost function according to the history of inconsistencies in the depth map, until convergence. While two graph-theoretic stereo algorithms are used in our experiments, our framework is general enough to be applied to many others. The validity of our framework is demonstrated using real imagery with different baselines.
ISBN:0769523722
9780769523729
ISSN:1063-6919
1063-6919
DOI:10.1109/CVPR.2005.168