A voting stereo matching method for real-time obstacle detection

Depth from stereo is one of the most active research areas in the computer vision field. The heavily investigated problem in stereo approaches is the matching between two or more images of a scene observed, by two or more video cameras, from different viewpoints. It consists of identifying features in the left and right images that are projections of the same physical feature in the three-dimensional world. This paper presents a real-time stereo matching method using a voting schema. The correspondence problem is first mapped onto a two-dimensional matrix, called matching matrix, where each element represents a possible match between two features extracted from the left and right images. Local and global constraints are then used to search the true elements of the matching matrix, which represent compatible matches. The valid elements are determined by applying the local constraints. Global constraints are used to define the voting rules between the valid elements. The voting based-method is evaluated for real-time obstacle detection in front of a moving car using linear stereo vision.