Abstract
This paper presents a new cooperative matching algorithm based on the integration of stereo and motion cues. In this algorithm, stereo disparity and image flow values are recovered from two successive pairs of stereo images by solving the stereo and motion correspondence problems. Feature points are extracted from the images as matching objects. The entire matching process composes of a network of four subprocesses (two for stereo and two for motion). Each of the subprocesses can access information from connected nodes to perform the disambiguation. The “best” matches are obtained in a relaxation manner using the 3-D continuity constraint. Experimental results are presented to illustrate the performances of the proposed method.
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