Issue No. 05 - May (2011 vol. 33)
Michael M. Bronstein , Technion - Israel Institute of Technology, Haifa
Alexander M. Bronstein , Tel-Aviv University, Tel-Aviv
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.
Diffusion distance, commute time, spectral distance, eigenmap, Laplace-Beltrami operator, heat kernel, distribution, global point signature, nonrigid shapes, similarity.
M. M. Bronstein and A. M. Bronstein, "Shape Recognition with Spectral Distances," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 33, no. , pp. 1065-1071, 2010.