Shape Recognition with Spectral Distances

  • Authors:
  • Michael M. Bronstein;Alexander M. Bronstein

  • Affiliations:
  • Technion - Israel Institute of Technology, Haifa;Tel-Aviv University, Tel-Aviv

  • Venue:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Year:
  • 2011

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Abstract

Recent works have shown the use of diffusion geometry for various pattern recognition applications, including nonrigid shape analysis. In this paper, we introduce spectral shape distance as a general framework for distribution-based shape similarity and show that two recent methods for shape similarity due to Rustamov and Mahmoudi and Sapiro are particular cases thereof.