Structural matching for stereo vision

An approach for solving the stereo correspondence problem is suggested that is based on extracting local image structures and matching similar structures between two images. The individual matches are represented as nodes in a graph. Arcs in this graph represent local photometric, geometrical, and topological similarities between the two images. Left/right correspondences are equivalent with sets of mutually compatible nodes, which are found as maximal cliques in the graph. The best clique selected according to an evaluation procedure is considered to be the best available match. An algorithm based on this approach is described and evaluated. Some experimental results obtained by applying this algorithm to a pair of images representing an indoor scene are reported