Functional correspondence by matrix completion

Artiom Kovnatsky, Michael M. Bronstein, Xavier Bresson, Pierre Vandergheynst

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

75 Scopus citations

Abstract

In this paper, we consider the problem of finding dense intrinsic correspondence between manifolds using the recently introduced functional framework. We pose the functional correspondence problem as matrix completion with manifold geometric structure and inducing functional localization with the L1 norm. We discuss efficient numerical procedures for the solution of our problem. Our method compares favorably to the accuracy of state-of-the-art correspondence algorithms on non-rigid shape matching benchmarks, and is especially advantageous in settings when only scarce data is available.

Original languageEnglish
Title of host publicationIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
PublisherIEEE Computer Society
Pages905-914
Number of pages10
ISBN (Electronic)9781467369640
DOIs
StatePublished - 14 Oct 2015
Externally publishedYes
EventIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015 - Boston, United States
Duration: 7 Jun 201512 Jun 2015

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume07-12-June-2015
ISSN (Print)1063-6919

Conference

ConferenceIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
Country/TerritoryUnited States
CityBoston
Period7/06/1512/06/15

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