3-D to 2-D Pose Determination with Regions

  • Authors:
  • David Jacobs;Ronen Basri

  • Affiliations:
  • NEC Research Institute, 4 Independence Way, Princeton, NJ 08540, USA. dwj@research.nj.nec.com;Department of Applied Math., The Weizmann Inst. of Science, Rehovot, 76100, Israel. ronen@wisdom.weizmann.ac.il

  • Venue:
  • International Journal of Computer Vision - Special issue on computer vision research at NEC Research Institute
  • Year:
  • 1999

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Abstract

This paper presents a novel approach to parts-based object recognitionin the presence of occlusion. We focus on the problem of determiningthe pose of a 3-D object from a single 2-D image when convex parts ofthe object have been matched to corresponding regions in the image. We consider three types of occlusions: self-occlusion, occlusionswhose locus is identified in the image, and completely arbitraryocclusions. We show that in the first two cases this is a convexoptimization problem, derive efficient algorithms, and characterize their performance. For the last case, we prove thatthe problem of finding valid poses is computationally hard, butprovide an efficient, approximate algorithm. This work generalizesour previous work on region-based object recognition, which focused onthe case of planar models.