Heat Kernels for Non-Rigid Shape Retrieval: Sparse Representation and Efficient Classification

Abstract

One of the major goals of computer vision and machine intelligence is the development of flexible and efficient methods for shape representation. This paper presents an approach for shape retrieval based on sparse representation of scale-invariant heat kernel. We use the Laplace-Beltrami eigen functions to detect a small number of critical points on the… (More)
DOI: 10.1109/CRV.2012.28