Stereo matching with mumford-shah regularization and occlusion handling

Rami Ben-Ari, Nir Sochen

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number5401165
Pages (from-to)2071-2084
Number of pages14
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume32
Issue number11
DOIs
StatePublished - 2010

Keywords

  • Mumford-Shah functional
  • Stereo matching
  • Total Variation
  • occlusion handling
  • variational stereo vision

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