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This paper describes a system which robustly estimates motion, and the 3D structure of a rigid environment, as a stereo vision platform moves through it. The system can cope with any camera motion, and any scene structure and is successful even in the presence of large jumps in camera position between the capture of successive image pairs, and when point matching is ambiguous. The system was developed to provide robust obstacle avoidance for a partially sighted person. The process described attempts to maximize use of the abundant information present in a stereo sequence. Key features include the use of multiple stereo match hypotheses, efficient motion computation from three images, and the use of this motion to ensure reliable matching, and to eliminate multiple stereo matches. Points are reconstructed in 3D space and tracked in a static coordinate frame with a Kalman Filter. This results in good 3D scene reconstructions. Structure which is impossible to match with certainty is absent, rather than being incorrectly reconstructed. As a result, the system is appropriate for obstacle detection. The results of processing some indoor and outdoor scenes, are given in the paper, and practical issues are highlighted throughout.

Original publication




Journal article


International Journal of Computer Vision

Publication Date





5 - 23