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Kullback Leibler Divergence Based Curve Matching Method

  • Pengwen Chen
  • Yunmei Chen
  • Murali Rao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4485)

Abstract

In this paper, we propose a variational model for curve matching based on Kullback-Leibler(KL) divergence. This framework accomplishes the difficult task of finding correspondences for a group of curves simultaneously in a symmetric and transitive fashion. Moreover the distance in the energy functional has the metric property. We also introduce a location weighted model to handle noise, distortion and occlusion. Numerical results indicate the effective of this framework. The existence of this model is also provided.

Keywords

Average Curve Kullback Leibler Divergence Angle Function Curve Match Bregman Divergence 
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 Berlin Heidelberg 2007

Authors and Affiliations

  • Pengwen Chen
    • 1
  • Yunmei Chen
    • 1
  • Murali Rao
    • 1
  1. 1.Department of Mathematics, University of Florida, Gainesville, FL,32611USA

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