Pairwise harmonics for shape analysis

Youyi Zheng, Chiewlan Tai, Eugene Zhang, Pengfei Xu

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

This paper introduces a simple yet effective shape analysis mechanism for geometry processing. Unlike traditional shape analysis techniques which compute descriptors per surface point up to certain neighborhoods, we introduce a shape analysis framework in which the descriptors are based on pairs of surface points. Such a pairwise analysis approach leads to a new class of shape descriptors that are more global, discriminative, and can effectively capture the variations in the underlying geometry. Specifically, we introduce new shape descriptors based on the isocurves of harmonic functions whose global maximum and minimum occur at the point pair. We show that these shape descriptors can infer shape structures and consistently lead to simpler and more efficient algorithms than the state-of-the-art methods for three applications: intrinsic reflectional symmetry axis computation, matching shape extremities, and simultaneous surface segmentation and skeletonization. © 2012 IEEE.
Original languageEnglish (US)
Pages (from-to)1172-1184
Number of pages13
JournalIEEE Transactions on Visualization and Computer Graphics
Volume19
Issue number7
DOIs
StatePublished - Jul 2013

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Software
  • Computer Vision and Pattern Recognition

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