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Conference Paper: A revisit to least squares orthogonal distance tting of parametric curves and surfaces

TitleA revisit to least squares orthogonal distance tting of parametric curves and surfaces
Authors
Liu, YWang, WP
KeywordsNonlinear Least Squares
Numerical Optimization
Orthogonal Distance Fitting
Parametric Curve And Surface Fitting
Issue Date2008
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
The 5th International Conference on Geometric Modeling and Processing (GMP 2008), Hangzhou, China, 23-25 April 2008. In Lecture Notes In Computer Science, 2008, v. 4975, p. 384-397 How to Cite?
DOI: http://dx.doi.org/10.1007/978-3-540-79246-8-29
AbstractFitting of data points by parametric curves and surfaces is demanded in many scientific fields. In this paper we review and analyze existing least squares orthogonal distance fitting techniques in a general numerical optimization framework. Two new geometric variant methods ( and ) are proposed. The geometric meanings of existing and modified optimization methods are also revealed. © 2008 Springer-Verlag Berlin Heidelberg.
Persistent Identifierhttp://hdl.handle.net/10722/93489
ISSN
0302-9743
2023 SCImago Journal Rankings: 0.606
References
References in Scopus

 

DC FieldValueLanguage
dc.contributor.authorLiu, Yen_HK
dc.contributor.authorWang, WPen_HK
dc.date.accessioned2010-09-25T15:02:42Z-
dc.date.available2010-09-25T15:02:42Z-
dc.date.issued2008en_HK
dc.identifier.citationThe 5th International Conference on Geometric Modeling and Processing (GMP 2008), Hangzhou, China, 23-25 April 2008. In Lecture Notes In Computer Science, 2008, v. 4975, p. 384-397-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10722/93489-
dc.description.abstractFitting of data points by parametric curves and surfaces is demanded in many scientific fields. In this paper we review and analyze existing least squares orthogonal distance fitting techniques in a general numerical optimization framework. Two new geometric variant methods ( and ) are proposed. The geometric meanings of existing and modified optimization methods are also revealed. © 2008 Springer-Verlag Berlin Heidelberg.-
dc.languageengen_HK
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/-
dc.relation.ispartofLecture Notes in Computer Scienceen_HK
dc.subjectNonlinear Least Squares-
dc.subjectNumerical Optimization-
dc.subjectOrthogonal Distance Fitting-
dc.subjectParametric Curve And Surface Fitting-
dc.titleA revisit to least squares orthogonal distance tting of parametric curves and surfacesen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailWang, WP: wenping@cs.hku.hken_HK
dc.identifier.authorityWang, WP=rp00186en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/978-3-540-79246-8-29-
dc.identifier.scopuseid_2-s2.0-67349121167-
dc.identifier.hkuros141125en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-67349121167&selection=ref&src=s&origin=recordpage-
dc.identifier.volume4975-
dc.identifier.spage384-
dc.identifier.epage397-
dc.publisher.placeGermany-
dc.identifier.scopusauthoridLiu, Y=27172089200-
dc.identifier.scopusauthoridWang, W=35147101600-
dc.customcontrol.immutablesml 160111 - merged-
dc.identifier.issnl0302-9743-

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