The wave kernel signature: A quantum mechanical approach to shape analysis

Mathieu Aubry, Ulrich Schlickewei, Daniel Cremers

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

675 Scopus citations

Abstract

We introduce the Wave Kernel Signature (WKS) for characterizing points on non-rigid three-dimensional shapes. The WKS represents the average probability of measuring a quantum mechanical particle at a specific location. By letting vary the energy of the particle, the WKS encodes and separates information from various different Laplace eigenfrequencies. This clear scale separation makes the WKS well suited for a large variety of applications. Both theoretically and in quantitative experiments we demonstrate that the WKS is substantially more discriminative and therefore allows for better feature matching than the commonly used Heat Kernel Signature (HKS). As an application of the WKS in shape analysis we show results on shape matching.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011
Pages1626-1633
Number of pages8
DOIs
StatePublished - 2011
Event2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011 - Barcelona, Spain
Duration: 6 Nov 201113 Nov 2011

Publication series

NameProceedings of the IEEE International Conference on Computer Vision

Conference

Conference2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011
Country/TerritorySpain
CityBarcelona
Period6/11/1113/11/11

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