CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 2010 vol.32 Issue No.11 - November
Issue No.11 - November (2010 vol.32)
Rami Ben-Ari , Orbotech Ltd., Yavneh
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2010.32
This paper addresses the problem of correspondence establishment in binocular stereo vision. We suggest a novel spatially continuous approach for stereo matching based on the variational framework. The proposed method suggests a unique regularization term based on Mumford-Shah functional for discontinuity preserving, combined with a new energy functional for occlusion handling. The evaluation process is based on concurrent minimization of two coupled energy functionals, one for domain segmentation (occluded versus visible) and the other for disparity evaluation. In addition to a dense disparity map, our method also provides an estimation for the half-occlusion domain and a discontinuity function allocating the disparity/depth boundaries. Two new constraints are introduced improving the revealed discontinuity map. The experimental tests include a wide range of real data sets from the Middlebury stereo database. The results demonstrate the capability of our method in calculating an accurate disparity function with sharp discontinuities and occlusion map recovery. Significant improvements are shown compared to a recently published variational stereo approach. A comparison on the Middlebury stereo benchmark with subpixel accuracies shows that our method is currently among the top-ranked stereo matching algorithms.
Stereo matching, Mumford-Shah functional, variational stereo vision, occlusion handling, Total Variation.
Rami Ben-Ari, "Stereo Matching with Mumford-Shah Regularization and Occlusion Handling", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.32, no. 11, pp. 2071-2084, November 2010, doi:10.1109/TPAMI.2010.32