DocumentCode
1398590
Title
Shape Recognition with Spectral Distances
Author
Bronstein, Michael M. ; Bronstein, Alexander M.
Author_Institution
Fac. of Inf., Univ. delta Svizzera Italiana, Lugano, Switzerland
Volume
33
Issue
5
fYear
2011
fDate
5/1/2011 12:00:00 AM
Firstpage
1065
Lastpage
1071
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;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/TPAMI.2010.210
Filename
5661779
Link To Document