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An algorithm to detect depth discontinuities from a stereo pair of images is presented. The algorithm matches individual pixels in corresponding scanline pairs while allowing occluded pixels to remain unmatched, then propagates the information between scanlines by means of a fast postprocessor. The algorithm handles large untextured regions, uses a measure of pixel dissimilarity that is insensitive to image sampling, and prunes bad search nodes to increase the speed of dynamic programming. The computation is relatively fast, taking about 1.5 microseconds per pixel per disparity on a workstation. Approximate disparity maps and precise depth discontinuities (along both horizontal and vertical boundaries) are shown for five stereo images containing textured, untextured, fronto-parallel, and slanted objects.
Birchfield et al. (Wed,) studied this question.