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dc.contributor.authorZheng, Youyi
dc.contributor.authorTai, Chiewlan
dc.contributor.authorZhang, Eugene
dc.contributor.authorXu, Pengfei
dc.date.accessioned2015-08-03T11:11:56Z
dc.date.available2015-08-03T11:11:56Z
dc.date.issued2013-07
dc.identifier.citationYouyi 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
dc.identifier.issn10772626
dc.identifier.pmid23661011
dc.identifier.doi10.1109/TVCG.2012.309
dc.identifier.urihttp://hdl.handle.net/10754/562832
dc.description.abstractThis 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.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectintrinsic symmetry
dc.subjectpairwise harmonics
dc.subjectsegmentation and skeletonization
dc.subjectShape analysis
dc.subjectshape correspondence
dc.titlePairwise harmonics for shape analysis
dc.typeArticle
dc.contributor.departmentVisual Computing Center (VCC)
dc.identifier.journalIEEE Transactions on Visualization and Computer Graphics
dc.contributor.institutionDepartment of Computer Science and Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
dc.contributor.institutionSchool of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331, United States
kaust.personZheng, Youyi


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