Stereo vision technique using neighborhood support criterion
Suya o. You, Jian Liu, Faguang Wan · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
Passively sensing three-dimensional structure by means of computational stereo has received a great deal of attention in the computer vision community as well as in the traditional photogrammetric and remote sensing communities. The first and most difficult step in recovering 3-D information from a pair of stereo images is that of matching points from one image of the pair to the corresponding points in the second image. In this paper we develop an edge-based, fast and effective stereo matching technique characterized by two matching stages: initial matching and consistency check. Several constraints (Epipolar, Uniqueness, Disparity continuity, Stochastic constraint and Disparity range constraint) are used to reduce the combinatorial search and the ambiguity of the false targets. With this approach, we can obtain the global optimum matches. The algorithm has been experimentally evaluated using a set of real images. The implementation and results have shown the efficacy of the proposed stereo matching technique.