Direct Estimation of Nonrigid Registrations with Image-Based Self-Occlusion Reasoning

  • Authors:
  • Vincent Gay-Bellile;Adrien Bartoli;Patrick Sayd

  • Affiliations:
  • CEA Saclay and LASMEA, UMR, CNRS/UBP, France;LASMEA, UMR, CNRS/UBP, France;CEA Saclay, France

  • Venue:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Year:
  • 2010

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Abstract

The registration problem for images of a deforming surface has been well studied. External occlusions are usually well handled. In 2D image-based registration, self-occlusions are more challenging. Consequently, the surface is usually assumed to be only slightly self-occluding. This paper is about image-based nonrigid registration with self-occlusion reasoning. A specific framework explicitly modeling self-occlusions is proposed. It is combined with an intensity-based, “direct” data term for registration. Self-occlusions are detected as shrinkage areas in the 2D warp. Experimental results on several challenging data sets show that our approach successfully registers images with self-occlusions while effectively detecting the self-occluded regions.