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Discrete Minimum Distortion Correspondence Problems for Non-rigid Shape Matching

  • Chaohui Wang
  • Michael M. Bronstein
  • Alexander M. Bronstein
  • Nikos Paragios
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6667)

Abstract

Similarity and correspondence are two fundamental archetype problems in shape analysis, encountered in numerous application in computer vision and pattern recognition. Many methods for shape similarity and correspondence boil down to the minimum-distortion correspondence problem, in which two shapes are endowed with certain structure, and one attempts to find the matching with smallest structure distortion between them. Defining structures invariant to some class of shape transformations results in an invariant minimum-distortion correspondence or similarity. In this paper, we model shapes using local and global structures, formulate the invariant correspondence problem as binary graph labeling, and show how different choice of structure results in invariance under various classes of deformations.

Keywords

Heat Kernel Geodesic Distance Shape Match Correspondence Problem Commute Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Chaohui Wang
    • 1
    • 2
  • Michael M. Bronstein
    • 3
  • Alexander M. Bronstein
    • 4
  • Nikos Paragios
    • 1
    • 2
  1. 1.Laboratoire MASEcole Centrale de ParisChâtenay-MalabryFrance
  2. 2.Equipe GALENINRIA Saclay - Île de FranceOrsayFrance
  3. 3.Institute of Computational Science, Faculty of InformaticsUniversità della Svizzera ItalianaLuganoSwitzerland
  4. 4.Department of Electrical EngineeringTel Aviv UniversityIsrael

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