A computational framework is introduced for matching a pair of stereo images which, in contrast to existing algorithms, features a self-contained local matching module cascaded with a global matching module. Local matching outputs a 3-D grey-scale image in which each and every point has an intensity measuring the goodness of a possible match. Global matching reduces to surface detection in this image. To detect the surface, it is first enhanced, employing a hyperpyramid data structure. Unlike traditional multiresolution approaches, which are based on the coarse-to-fine continuation method, the authors' multilevel method emphasizes a fine-to-coarse process in which local support is accumulated. The algorithm is concise, efficient and above all, gives good results for complex scenes.<>


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    Title :

    Local, global, and multilevel stereo matching


    Contributors:
    Yang, Y. (author) / Yuille, A. (author) / Lu, J. (author)


    Publication date :

    1993-01-01


    Size :

    561495 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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