Positioning three-dimensional objects using stereo images

A simple stereo algorithm is presented for determining the three-dimensional position of object points in a scene. In this algorithm two independent measures of similarity, the zero-crossing pattern and the intensity gradient, are combined to improve the matching process. Zero-crossing neighborhoods are classified into 16 possible patterns according to their local connectivity. In the matching process a relaxation method is used to find the best matches. Three constraints are incorporated into a single relaxation process, namely, disparity continuity, figural continuity, and smoothness of the probability of matching.

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