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A Comparison Study on Two Multi-scale Shape Matching Schemes

  • Bo Li
  • Henry Johan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5359)

Abstract

We present and compare two multi-scale shape matching schemes: Chi-square distance based scheme and pyramid matching mode based scheme. We define a shape as a set of points. Multi-scale shape matching includes two steps: multi-scale feature extraction and point correspondence. We define a hybrid feature for every point by combining a global multi-scale shape context feature and a local variation feature. The two schemes have a difference in the computation of multi-scale shape context feature distance: the Chi-square distance based scheme directly sums up weighted Chi-square distances at different scales while the pyramid matching mode based scheme utilizes a multi-scale pyramid matching mode. Experimental results based on Frenkel and Kimia databases show that: (1) the pyramid matching mode based scheme can achieve robust and often better performance than the Chi-square distance based scheme; (2) the proposed two multi-scale schemes can achieve averagely better results than the single scale schemes.

Keywords

Subsection Scheme Shape Context Hybrid Feature Histogram Intersection Fast March Method 
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 2008

Authors and Affiliations

  • Bo Li
    • 1
  • Henry Johan
    • 1
  1. 1.School of Computer EngineeringNanyang Technological UniversitySingapore

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