Shape recognition with spectral distances

Michael M Bronstein; Alexander M Bronstein

doi:10.1109/TPAMI.2010.210

Shape recognition with spectral distances

IEEE Trans Pattern Anal Mach Intell. 2011 May;33(5):1065-71. doi: 10.1109/TPAMI.2010.210.

Authors

Michael M Bronstein¹, Alexander M Bronstein

Affiliation

¹ Institute of Computational Science, Faculty of Informatics, Università della Svizzera Italiana, Lugano 6900, Switzerland. michael.bronstein@usi.ch

PMID: 21135442
DOI: 10.1109/TPAMI.2010.210

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.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.