期刊
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
卷 19, 期 7, 页码 1172-1184出版社
IEEE COMPUTER SOC
DOI: 10.1109/TVCG.2012.309
关键词
Shape analysis; pairwise harmonics; intrinsic symmetry; shape correspondence; segmentation and skeletonization
资金
- Hong Kong Research Grant Council [GRF619611, GRF619012]
- National Science Foundation [IIS-0917308]
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [0917308] Funding Source: National Science Foundation
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.
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