@article{8fcef78b29bc408f910433bb675fbf54,
title = "Shape recognition with spectral distances",
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 = "Diffusion distance, Laplace-Beltrami operator, commute time, distribution, eigenmap, global point signature, heat kernel, nonrigid shapes, similarity, spectral distance",
author = "Bronstein, \{Michael M.\} and Bronstein, \{Alexander M.\}",
note = "Funding Information: The authors are grateful to Ron Kimmel, Radu Horaud, and Guillermo Sapiro for insightful discussions. This research was supported in part by the Office of Naval Research Grant.",
year = "2011",
doi = "10.1109/TPAMI.2010.210",
language = "אנגלית",
volume = "33",
pages = "1065--1071",
journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
issn = "0162-8828",
publisher = "IEEE Computer Society",
number = "5",
}