Inference of Segmented Overlapping Surfaces from Binocular Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Simple Stereo Algorithm to Recover Precise Object Boundaries and Smooth Surfaces
International Journal of Computer Vision
Inferring Segmented Surface Description from Stereo Data
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Advances in Computational Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stereo Using Monocular Cues within the Tensor Voting Framework
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Real-Time Occlusion Aware Hardware Structure for Disparity Map Computation
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Coarse-to-fine stereo vision with accurate 3D boundaries
Image and Vision Computing
Complex correlation statistic for dense stereoscopic matching
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
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We study occluding contour artifacts in area-based stereo matching: they are false responses of the matching operator to the occlusion boundary and cause the objects extend beyond their true boundaries in disparity maps. Most of the matching methods suffer from these artifacts; the effect is so strong that it cannot be ignored. We show what gives rise to the artifacts and design a matching criterion that accommodates the presence of occlusions as opposed to methods that identify and remove the artifacts. This approach leads to the problem of measurement contamination studied in statistics. We show that such a problem is hard given finite computational resources, unless more independent measurements directly related to occluding contours is available. What can be achieved is a substantial reduction of the artifacts, especially for large matching templates. Reduced artifacts allow for easier hierarchical matching and for easy fusion of reconstructions from different viewpoints into a coherent whole.