Presentation 2001/12/14
Discrete Variational Problem for Surface Fitting to a Cloud of Noisy Sample Points
Atsushi IMIYA, Hisashi OOTANI,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In this paper, we propose a method for estimation of a surface from cloud of noisy samples. We formulate the variational method for the collection of sample points. And we derive a numerical method for the computation of approximated solution. The criterion for our variational problem basically depends on distance measure and angles between portions of a polyhedral surface. The distance measure controls the convergence of criterion locally, while the angle measure controls the convergence of the criterion globally. The criterion is also valid for the k-dimensional manifold in n-dimensional Euclidean space for k < n. Since our method automatically learns the topology of the collection sample points, first assuming it topology as an open surface, second evaluating a condition, and third detecting the correct topology of a sample cloud which expresses the geometrical concept.
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Keyword(in English) Variational method / Surface fitting / Principal surface / Median axes / Machine learning / Topology
Paper # PRMU2001-179
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Conference Information
Committee PRMU
Conference Date 2001/12/14(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Discrete Variational Problem for Surface Fitting to a Cloud of Noisy Sample Points
Sub Title (in English)
Keyword(1) Variational method
Keyword(2) Surface fitting
Keyword(3) Principal surface
Keyword(4) Median axes
Keyword(5) Machine learning
Keyword(6) Topology
1st Author's Name Atsushi IMIYA
1st Author's Affiliation Institute of Media and Information Technology, Chiba University()
2nd Author's Name Hisashi OOTANI
2nd Author's Affiliation School of Science and Technology, Chiba University
Date 2001/12/14
Paper # PRMU2001-179
Volume (vol) vol.101
Number (no) 525
Page pp.pp.-
#Pages 8
Date of Issue