Abstract: This paper examines the problem of matching corresponding object points in three views of a scene. The matching problem is a critical step in the recovery of 3-dimensional position by stereo image processing and has important application in the analysis of particle distributions and fluid flows. We introduce an algorithms that iteratively searches for all possible pairwise matches using trinocular consistency constraints. The algorithm is shown to be equivalent to a search for edges that belong to all perfect matchings in a bipartite graph that links consistent matches between two views. Three such problems are solved in parallel. An attractive property of the matching algorithm is its graceful degradation in response to image distortion and modeling error. Although measurement errors may prevent successful matching, wrong matches can almost always be avoided if the error in the image position of a particle can be bounded. Thus, noise can cause a loss of acuity but should not cause the introduction of gross misinformation that could result from incorrect matching. Experiments with synthetic particle images demonstrate that this approach can lead to significantly greater numbers of matches than algorithms that match in a single direction.!13
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