Stereo Correspondence Through Feature Grouping and Maximal Cliques

Abstract : In this paper we propose a method to solve the stereo correspondence problem. The method matches features and feature relationships and can be paraphrased as follows. Linear edge segments are extracted from both the left and right images. Each such segment is characterized by its position and orientation in the image as well as its relationsphip with the nearby segments. A relational graph is thus built from each image. For each segment in one image a set of potential assignments in the other image is determined. These assignments are represented as nodes in a correspondence graph. Arcs in this graph represent compatible assignments established on the basis of segment relationships. Stereo matching becomes equivalent to searching for sets of mutually compatible nodes in this graph. These sets are found by looking for maximal cliques. The maximal clique the best suited to represent a stereo correspondence is selected using a benefit function. Finally we show numerous results obtained with this method.
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IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 1989, 11 (11), pp.1168--1180. 〈10.1109/34.42855〉
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Radu Horaud, Thomas Skordas. Stereo Correspondence Through Feature Grouping and Maximal Cliques. IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 1989, 11 (11), pp.1168--1180. 〈10.1109/34.42855〉. 〈inria-00589991〉

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