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Stereo Matching with Color-Weighted Correlation, Hierarchical Belief Propagation, and Occlusion Handling
March 2009 (vol. 31 no. 3)
pp. 492-504
Qingxiong Yang, University of Illinois at Urbana Champaign, Urbana
Liang Wang, University of Kentucky, Lexington
Ruigang Yang, University of Kentucky, Lexington
Henrik Stewénius, Google Switzerland, Zurich
David Nistér, Microsoft Corp., Redmond
In this paper, we formulate a stereo matching algorithm with careful handling of disparity, discontinuity and occlusion. The algorithm works with a global matching stereo model based on an energy-minimization framework. The global energy contains two terms, the data term and the smoothness term. The data term is first approximated by a color-weighted correlation, then refined in occluded and low-texture areas in a {\it{repeated}} application of a hierarchical loopy belief propagation algorithm. The experimental results are evaluated on the Middlebury data sets, showing that our algorithm is the {\it{top}} performer among all the algorithms listed there.

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Index Terms:
3D/stereo scene analysis, Segmentation, Markov random fields
Citation:
Qingxiong Yang, Liang Wang, Ruigang Yang, Henrik Stewénius, David Nistér, "Stereo Matching with Color-Weighted Correlation, Hierarchical Belief Propagation, and Occlusion Handling," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 3, pp. 492-504, March 2009, doi:10.1109/TPAMI.2008.99
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