Pairwise harmonics for shape analysis

Handle URI:
http://hdl.handle.net/10754/562832
Title:
Pairwise harmonics for shape analysis
Authors:
Zheng, Youyi; Tai, Chiewlan; Zhang, Eugene; Xu, Pengfei
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.
KAUST Department:
Visual Computing Center (VCC)
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Transactions on Visualization and Computer Graphics
Issue Date:
Jul-2013
DOI:
10.1109/TVCG.2012.309
Type:
Article
ISSN:
10772626
Appears in Collections:
Articles; Visual Computing Center (VCC)

Full metadata record

DC FieldValue Language
dc.contributor.authorZheng, Youyien
dc.contributor.authorTai, Chiewlanen
dc.contributor.authorZhang, Eugeneen
dc.contributor.authorXu, Pengfeien
dc.date.accessioned2015-08-03T11:11:56Zen
dc.date.available2015-08-03T11:11:56Zen
dc.date.issued2013-07en
dc.identifier.issn10772626en
dc.identifier.doi10.1109/TVCG.2012.309en
dc.identifier.urihttp://hdl.handle.net/10754/562832en
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.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectintrinsic symmetryen
dc.subjectpairwise harmonicsen
dc.subjectsegmentation and skeletonizationen
dc.subjectShape analysisen
dc.subjectshape correspondenceen
dc.titlePairwise harmonics for shape analysisen
dc.typeArticleen
dc.contributor.departmentVisual Computing Center (VCC)en
dc.identifier.journalIEEE Transactions on Visualization and Computer Graphicsen
dc.contributor.institutionDepartment of Computer Science and Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kongen
dc.contributor.institutionSchool of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331, United Statesen
kaust.authorZheng, Youyien
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