Title :
Shape Recognition with Spectral Distances
Author :
Bronstein, Michael M. ; Bronstein, Alexander M.
Author_Institution :
Fac. of Inf., Univ. delta Svizzera Italiana, Lugano, Switzerland
fDate :
5/1/2011 12:00:00 AM
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.
Keywords :
geometry; shape recognition; diffusion geometry; distribution-based shape similarity; nonrigid shape analysis; pattern recognition; shape recognition; spectral shape distance; Eigenvalues and eigenfunctions; Geometry; Heating; Kernel; Measurement; Shape; Transfer functions; Diffusion distance; Laplace-Beltrami operator; commute time; distribution; eigenmap; global point signature; heat kernel; nonrigid shapes; similarity.; spectral distance;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2010.210
