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Article: A quasi-Monte Carlo method for computing areas of point-sampled surfaces

TitleA quasi-Monte Carlo method for computing areas of point-sampled surfaces
Authors
KeywordsPoint-sampled surfaces
Area
Quasi-Monte Carlo methods
Intersection
Issue Date2006
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/cad
Citation
Computer-Aided Design, 2006, v. 38 n. 1, p. 55-68 How to Cite?
AbstractA novel and efficient quasi-Monte Carlo method for computing the area of a point-sampled surface with associated surface normal for each point is presented. Our method operates directly on the point cloud without any surface reconstruction procedure. Using the Cauchy–Crofton formula, the area of the point-sampled surface is calculated by counting the number of intersection points between the point cloud and a set of uniformly distributed lines generated with low-discrepancy sequences. Based on a clustering technique, we also propose an effective algorithm for computing the intersection points of a line with the point-sampled surface. By testing on a number of point-based models, experiments suggest that our method is more robust and more efficient than those conventional approaches based on surface reconstruction.
Persistent Identifierhttp://hdl.handle.net/10722/48419
ISSN
2015 Impact Factor: 2.149
2015 SCImago Journal Rankings: 1.078
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLiu, YSen_HK
dc.contributor.authorYong, JHen_HK
dc.contributor.authorZhang, Hen_HK
dc.contributor.authorYan, DMen_HK
dc.contributor.authorSun, JGen_HK
dc.date.accessioned2008-05-22T04:12:31Z-
dc.date.available2008-05-22T04:12:31Z-
dc.date.issued2006en_HK
dc.identifier.citationComputer-Aided Design, 2006, v. 38 n. 1, p. 55-68en_HK
dc.identifier.issn0010-4485en_HK
dc.identifier.urihttp://hdl.handle.net/10722/48419-
dc.description.abstractA novel and efficient quasi-Monte Carlo method for computing the area of a point-sampled surface with associated surface normal for each point is presented. Our method operates directly on the point cloud without any surface reconstruction procedure. Using the Cauchy–Crofton formula, the area of the point-sampled surface is calculated by counting the number of intersection points between the point cloud and a set of uniformly distributed lines generated with low-discrepancy sequences. Based on a clustering technique, we also propose an effective algorithm for computing the intersection points of a line with the point-sampled surface. By testing on a number of point-based models, experiments suggest that our method is more robust and more efficient than those conventional approaches based on surface reconstruction.en_HK
dc.format.extent2024005 bytes-
dc.format.extent3238 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/caden_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectPoint-sampled surfacesen_HK
dc.subjectAreaen_HK
dc.subjectQuasi-Monte Carlo methodsen_HK
dc.subjectIntersectionen_HK
dc.titleA quasi-Monte Carlo method for computing areas of point-sampled surfacesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0010-4485&volume=38&issue=1&spage=55&epage=68&date=2006&atitle=A+quasi-Monte+Carlo+method+for+computing+areas+of+point-sampled+surfacesen_HK
dc.identifier.emailZhang, H: hzhang@cs.hku.hken_HK
dc.identifier.emailYan, DM: dmyan@cs.hku.hken_HK
dc.description.naturepostprinten_HK
dc.identifier.doi10.1016/j.cad.2005.07.002en_HK
dc.identifier.scopuseid_2-s2.0-26444619391-
dc.identifier.hkuros122109-
dc.identifier.isiWOS:000233192700006-

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