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Conference Paper: Fitting subdivision surfaces to unorganized point data using SDM

TitleFitting subdivision surfaces to unorganized point data using SDM
Authors
Issue Date2004
PublisherIEEE, Computer Society.
Citation
Proceedings - Pacific Conference On Computer Graphics And Applications, 2004, p. 16-24 How to Cite?
AbstractWe study the reconstruction of smooth surfaces from point clouds. We use a new squared distance error term in optimization to fit a subdivision surface to a set of unorganized points, which defines a closed target surface of arbitrary topology. The resulting method is based on the framework of squared distance minimization (SDM) proposed by Pottmann et al. Specifically, with an initial subdivision surface having a coarse control mesh as input, we adjust the control points by optimizing an objective function through iterative minimization of a quadratic approximant of the squared distance function of the target shape. Our experiments show that the new method (SDM) converges much faster than the commonly used optimization method using the point distance error function, which is known to have only linear convergence. This observation is further supported by our recent result that SDM can be derived from the Newton method with necessary modifications to make the Hessian positive definite and the fact that the Newton method has quadratic convergence. © 2004 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/146204
ISSN
References
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DC FieldValueLanguage
dc.contributor.authorCheng, KSDen_HK
dc.contributor.authorWang, Wen_HK
dc.contributor.authorQin, Hen_HK
dc.contributor.authorWong, KYKen_HK
dc.contributor.authorYang, Hen_HK
dc.contributor.authorLiu, Yen_HK
dc.date.accessioned2012-04-05T04:11:35Z-
dc.date.available2012-04-05T04:11:35Z-
dc.date.issued2004en_HK
dc.identifier.citationProceedings - Pacific Conference On Computer Graphics And Applications, 2004, p. 16-24en_HK
dc.identifier.issn1550-4085en_HK
dc.identifier.urihttp://hdl.handle.net/10722/146204-
dc.description.abstractWe study the reconstruction of smooth surfaces from point clouds. We use a new squared distance error term in optimization to fit a subdivision surface to a set of unorganized points, which defines a closed target surface of arbitrary topology. The resulting method is based on the framework of squared distance minimization (SDM) proposed by Pottmann et al. Specifically, with an initial subdivision surface having a coarse control mesh as input, we adjust the control points by optimizing an objective function through iterative minimization of a quadratic approximant of the squared distance function of the target shape. Our experiments show that the new method (SDM) converges much faster than the commonly used optimization method using the point distance error function, which is known to have only linear convergence. This observation is further supported by our recent result that SDM can be derived from the Newton method with necessary modifications to make the Hessian positive definite and the fact that the Newton method has quadratic convergence. © 2004 IEEE.en_HK
dc.languageeng-
dc.publisherIEEE, Computer Society.-
dc.relation.ispartofProceedings - Pacific Conference on Computer Graphics and Applicationsen_HK
dc.rights12th Pacific Conference on Computer Graphics and Applications Proceedings. Copyright © IEEE, Computer Society.-
dc.rights©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleFitting subdivision surfaces to unorganized point data using SDMen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailWang, W:wenping@cs.hku.hken_HK
dc.identifier.emailWong, KYK:kykwong@cs.hku.hken_HK
dc.identifier.authorityWang, W=rp00186en_HK
dc.identifier.authorityWong, KYK=rp01393en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/PCCGA.2004.1348330en_HK
dc.identifier.scopuseid_2-s2.0-17444373155en_HK
dc.identifier.hkuros96730-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-17444373155&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage16en_HK
dc.identifier.epage24en_HK
dc.publisher.placeUnited Statesen_HK
dc.relation.projectOutdoor 3D scanner using off-the-shelf digital camera-
dc.identifier.scopusauthoridCheng, KSD=21733550700en_HK
dc.identifier.scopusauthoridWang, W=35147101600en_HK
dc.identifier.scopusauthoridQin, H=34974717300en_HK
dc.identifier.scopusauthoridWong, KYK=24402187900en_HK
dc.identifier.scopusauthoridYang, H=15137870100en_HK
dc.identifier.scopusauthoridLiu, Y=36064444100en_HK
dc.identifier.citeulike3776529-

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