Institute of Computational Science, Faculty of Informatics, Università della Svizzera Italiana, Lugano 6900, Switzerland.
IEEE Trans Pattern Anal Mach Intell. 2011 May;33(5):1065-71. doi: 10.1109/TPAMI.2010.210.
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.
最近的研究表明,扩散几何在各种模式识别应用中都有应用,包括非刚性形状分析。在本文中,我们提出了谱形状距离作为基于分布的形状相似度的一般框架,并证明了 Rustamov 和 Mahmoudi 以及 Sapiro 提出的两种最近的形状相似度方法是其特例。