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Pairwise harmonics for shape analysis
Pairwise harmonics for shape analysis
Type
Article
Authors
Zheng, Youyi
Tai, Chiewlan
Zhang, Eugene
Xu, Pengfei
KAUST Department
Visual Computing Center (VCC)
Date
2013-07
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.
Citation
Youyi Zheng, Chiew-Lan Tai, Zhang, E., & Pengfei Xu. (2013). Pairwise Harmonics for Shape Analysis. IEEE Transactions on Visualization and Computer Graphics, 19(7), 1172–1184. doi:10.1109/tvcg.2012.309
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Journal
IEEE Transactions on Visualization and Computer Graphics
DOI
10.1109/TVCG.2012.309
PubMed ID
23661011
Permanent link to this record
http://hdl.handle.net/10754/562832
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