Abstract
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 600 nanoseconds per pixel per disparity on a personal computer. Approximate disparity maps and precise depth discontinuities (along both horizontal and vertical boundaries) are shown for several stereo image pairs containing textured, untextured, fronto-parallel, and slanted objects in indoor and outdoor scenes.
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Birchfield, S., Tomasi, C. Depth Discontinuities by Pixel-to-Pixel Stereo. International Journal of Computer Vision 35, 269–293 (1999). https://doi.org/10.1023/A:1008160311296
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DOI: https://doi.org/10.1023/A:1008160311296