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Shape Segmentation and Matching with Flow Discretization

  • Tamal K. Dey
  • Joachim Giesen
  • Samrat Goswami
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2748)

Abstract

Geometric shapes are identified with their features. For computational purposes a concrete mathematical definition of features is required. In this paper we use a topological approach, namely dynamical systems, to define features of shapes. To exploit this definition algorithmically we assume that a point sample of the shape is given as input from which features of the shape have to be approximated. We translate our definition of features to the discrete domain while mimicking the set-up developed for the continuous shapes. Experimental results show that our algorithms segment shapes in two and three dimensions into so-called features quite effectively. Further, we develop a shape matching algorithm that takes advantage of our robust feature segmentation step.

Keywords

Distance Function Voronoi Diagram Stable Manifold Voronoi Cell Shape Match 
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 2003

Authors and Affiliations

  • Tamal K. Dey
    • 1
  • Joachim Giesen
    • 2
  • Samrat Goswami
    • 1
  1. 1.The Ohio State U.ColumbusUSA
  2. 2.ETH ZürichZürichSwitzerland

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