A correspondence-less approach to matching of deformable shapes

Jonathan Pokrass*, Alexander M. Bronstein, Michael M. Bronstein

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Finding a match between partially available deformable shapes is a challenging problem with numerous applications. The problem is usually approached by computing local descriptors on a pair of shapes and then establishing a point-wise correspondence between the two. In this paper, we introduce an alternative correspondence-less approach to matching fragments to an entire shape undergoing a non-rigid deformation. We use diffusion geometric descriptors and optimize over the integration domains on which the integral descriptors of the two parts match. The problem is regularized using the Mumford-Shah functional. We show an efficient discretization based on the Ambrosio-Tortorelli approximation generalized to triangular meshes. Experiments demonstrating the success of the proposed method are presented.

Original languageEnglish
Title of host publicationScale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Revised Selected Papers
Pages592-603
Number of pages12
DOIs
StatePublished - 2012
Externally publishedYes
Event3rd International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2011 - Ein-Gedi, Israel
Duration: 29 May 20112 Jun 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6667 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2011
Country/TerritoryIsrael
CityEin-Gedi
Period29/05/112/06/11

Keywords

  • Laplace-Beltrami operator
  • Mumford-Shah regularization
  • deformable shapes
  • diffusion geometry
  • heat kernel signature
  • partial correspondence
  • partial matching
  • partial similarity
  • shape descriptors

Fingerprint

Dive into the research topics of 'A correspondence-less approach to matching of deformable shapes'. Together they form a unique fingerprint.

Cite this