Stereo correspondence using a genetic scheme with a new solution encoding

Stereo vision is a popular approach allowing to compute 3D structure of a scene seen by two or more video cameras from different viewpoints. The heavily investigated problem in this approach is the stereo matching problem. We present a new genetic scheme to the correspondence problem where a new solution encoding is proposed. To evaluate a solution, the fitness function is defined from three competing constraints, such that best matches correspond to its minima. Experimental results are presented to demonstrate the effectiveness of the proposed approach for extracting depth information from stereo linear images.