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Correspondences of Persistent Feature Points on Near-Isometric Surfaces

  • Ying Yang
  • David Günther
  • Stefanie Wuhrer
  • Alan Brunton
  • Ioannis Ivrissimtzis
  • Hans-Peter Seidel
  • Tino Weinkauf
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7583)

Abstract

We present a full pipeline for finding corresponding points between two surfaces based on conceptually simple and computationally efficient components. Our pipeline begins with robust and stable extraction of feature points from the surfaces. We then find a set of near isometric correspondences between the feature points by solving an optimization problem using established components. The performance is evaluated on a large number of 3D models from the following perspectives: robustness w.r.t. isometric deformation, robustness w.r.t. noise and incomplete surfaces, partial matching, and anisometric deformation.

Keywords

Feature Point Gaussian Curvature Markov Random Field Partial Match Heat Kernel Signature 
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

  • Ying Yang
    • 1
    • 2
  • David Günther
    • 1
    • 3
  • Stefanie Wuhrer
    • 3
    • 1
  • Alan Brunton
    • 3
    • 4
  • Ioannis Ivrissimtzis
    • 2
  • Hans-Peter Seidel
    • 1
  • Tino Weinkauf
    • 1
  1. 1.MPI InformatikSaarbrückenGermany
  2. 2.Durham UniversityDurhamUK
  3. 3.Saarland UniversitySaarbrückenGermany
  4. 4.University of OttawaOttawaCanada

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