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Segment-Based Stereo Matching Using Belief Propagation and a Self-Adapting Dissimilarity Measure

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Segment-Based Stereo Matching Using Belief Propagation and a Self-Adapting Dissimilarity Measure
A novel stereo matching algorithm is proposed that utilizes color segmentation on the reference image and a selfadapting matching score that maximizes the number of reliable correspondences. The scene structure is modeled by a set of planar surface patches which are estimated using a new technique that is more robust to outliers. Instead of assigning a disparity value to each pixel, a disparity plane is assigned to each segment. The optimal disparity plane labeling is approximated by applying belief propagation. Experimental results using the Middlebury stereo test bed demonstrate the superior performance of the proposed method.
Andreas Klaus, Mario Sormann, Konrad F. Karner
Added 11 Jun 2010
Updated 11 Jun 2010
Type Conference
Year 2006
Where ICPR
Authors Andreas Klaus, Mario Sormann, Konrad F. Karner
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