A Condition Number for Non-Rigid Shape Matching

Maks Ovsjanikov, Qi-Xing Huang, Leonidas Guibas

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

© 2011 The Author(s). Despite the large amount of work devoted in recent years to the problem of non-rigid shape matching, practical methods that can successfully be used for arbitrary pairs of shapes remain elusive. In this paper, we study the hardness of the problem of shape matching, and introduce the notion of the shape condition number, which captures the intuition that some shapes are inherently more difficult to match against than others. In particular, we make a connection between the symmetry of a given shape and the stability of any method used to match it while optimizing a given distortion measure. We analyze two commonly used classes of methods in deformable shape matching, and show that the stability of both types of techniques can be captured by the appropriate notion of a condition number. We also provide a practical way to estimate the shape condition number and show how it can be used to guide the selection of landmark correspondences between shapes. Thus we shed some light on the reasons why general shape matching remains difficult and provide a way to detect and mitigate such difficulties in practice.
Original languageEnglish (US)
Pages (from-to)1503-1512
Number of pages10
JournalComputer Graphics Forum
Volume30
Issue number5
DOIs
StatePublished - Aug 4 2011
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work was supported by NSF grants CCF 1011228, a KAUST-Stanford AEA grant, and a Stanford Graduate Fellowship. We also thank the anonymous reviewers for the valuable comments and suggestions.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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