Paretian Similarity for Partial Comparison of Non-rigid Objects

In this paper, we address the problem of partial comparison of non-rigid objects. We introduce a new class of set-valued distances, related to the concept of Pareto optimality in economics. Such distances allow to capture intrinsic geometric similarity between parts of non-rigid objects, obtaining semantically meaningful comparison results. The numerical implementation of our method is computationally efficient and is similar to GMDS, a multidimensional scaling-like continuous optimization problem.

• Type: Conference
• Year: 2007
• Where: SCALESPACE
• Authors: Alexander M. Bronstein, Michael M. Bronstein, Alfred M. Bruckstein, Ron Kimmel
• Keywords: Intrinsic Geometric Similarity, Non-Rigid Objects, SCALESPACE 2007, Set-valued Distances