Principal component and Voronoi skeleton alternatives for curve reconstruction from noisy point sets

Surface reconstruction from noisy point samples must take into consideration the stochastic nature of the sample -- In other words, geometric algorithms reconstructing the surface or curve should not insist in following in a literal way each sampled point -- Instead, they must interpret the sample a...

Full description

Autores:
Ruíz, Óscar
Vanegas, Carlos
Cadavid, Carlos
Tipo de recurso:
Fecha de publicación:
2007
Institución:
Universidad EAFIT
Repositorio:
Repositorio EAFIT
Idioma:
eng
OAI Identifier:
oai:repository.eafit.edu.co:10784/9689
Acceso en línea:
http://hdl.handle.net/10784/9689
Palabra clave:
GRÁFICOS POR COMPUTADOR
TOPOLOGÍA
Topology
Computer graphics
Topology
Computer graphics
Triangulación de Delaunay
Ingeniería inversa
Diagramas de Voronoi
Reconstrucción superficial
Reconstrucción 3D
Rights
License
Acceso abierto
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oai_identifier_str oai:repository.eafit.edu.co:10784/9689
network_acronym_str REPOEAFIT2
network_name_str Repositorio EAFIT
repository_id_str
dc.title.eng.fl_str_mv Principal component and Voronoi skeleton alternatives for curve reconstruction from noisy point sets
title Principal component and Voronoi skeleton alternatives for curve reconstruction from noisy point sets
spellingShingle Principal component and Voronoi skeleton alternatives for curve reconstruction from noisy point sets
GRÁFICOS POR COMPUTADOR
TOPOLOGÍA
Topology
Computer graphics
Topology
Computer graphics
Triangulación de Delaunay
Ingeniería inversa
Diagramas de Voronoi
Reconstrucción superficial
Reconstrucción 3D
title_short Principal component and Voronoi skeleton alternatives for curve reconstruction from noisy point sets
title_full Principal component and Voronoi skeleton alternatives for curve reconstruction from noisy point sets
title_fullStr Principal component and Voronoi skeleton alternatives for curve reconstruction from noisy point sets
title_full_unstemmed Principal component and Voronoi skeleton alternatives for curve reconstruction from noisy point sets
title_sort Principal component and Voronoi skeleton alternatives for curve reconstruction from noisy point sets
dc.creator.fl_str_mv Ruíz, Óscar
Vanegas, Carlos
Cadavid, Carlos
dc.contributor.department.spa.fl_str_mv Universidad EAFIT. Departamento de Ingeniería Mecánica
dc.contributor.author.none.fl_str_mv Ruíz, Óscar
Vanegas, Carlos
Cadavid, Carlos
dc.contributor.researchgroup.spa.fl_str_mv Laboratorio CAD/CAM/CAE
dc.subject.lemb.spa.fl_str_mv GRÁFICOS POR COMPUTADOR
TOPOLOGÍA
topic GRÁFICOS POR COMPUTADOR
TOPOLOGÍA
Topology
Computer graphics
Topology
Computer graphics
Triangulación de Delaunay
Ingeniería inversa
Diagramas de Voronoi
Reconstrucción superficial
Reconstrucción 3D
dc.subject.keyword.spa.fl_str_mv Topology
Computer graphics
dc.subject.keyword.eng.fl_str_mv Topology
Computer graphics
dc.subject.keyword..keywor.fl_str_mv Triangulación de Delaunay
Ingeniería inversa
Diagramas de Voronoi
Reconstrucción superficial
Reconstrucción 3D
description Surface reconstruction from noisy point samples must take into consideration the stochastic nature of the sample -- In other words, geometric algorithms reconstructing the surface or curve should not insist in following in a literal way each sampled point -- Instead, they must interpret the sample as a “point cloud” and try to build the surface as passing through the best possible (in the statistical sense) geometric locus that represents the sample -- This work presents two new methods to find a Piecewise Linear approximation from a Nyquist-compliant stochastic sampling of a quasi-planar C1 curve C(u) : R → R3, whose velocity vector never vanishes -- One of the methods articulates in an entirely new way Principal Component Analysis (statistical) and Voronoi-Delaunay (deterministic) approaches -- It uses these two methods to calculate the best possible tape-shaped polygon covering the planarised point set, and then approximates the manifold by the medial axis of such a polygon -- The other method applies Principal Component Analysis to find a direct Piecewise Linear approximation of C(u) -- A complexity comparison of these two methods is presented along with a qualitative comparison with previously developed ones -- It turns out that the method solely based on Principal Component Analysis is simpler and more robust for non self-intersecting curves -- For self-intersecting curves the Voronoi-Delaunay based Medial Axis approach is more robust, at the price of higher computational complexity -- An application is presented in Integration of meshes originated in range images of an art piece -- Such an application reaches the point of complete reconstruction of a unified mesh
publishDate 2007
dc.date.issued.none.fl_str_mv 2007-10
dc.date.available.none.fl_str_mv 2016-11-18T22:23:37Z
dc.date.accessioned.none.fl_str_mv 2016-11-18T22:23:37Z
dc.type.eng.fl_str_mv info:eu-repo/semantics/article
article
info:eu-repo/semantics/publishedVersion
publishedVersion
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.local.spa.fl_str_mv Artículo
status_str publishedVersion
dc.identifier.issn.none.fl_str_mv 0954-4828
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10784/9689
dc.identifier.doi.none.fl_str_mv 10.1080/09544820701403771
identifier_str_mv 0954-4828
10.1080/09544820701403771
url http://hdl.handle.net/10784/9689
dc.language.iso.eng.fl_str_mv eng
language eng
dc.relation.ispartof.spa.fl_str_mv Journal of Engineering Design, Volume 18, Issue 5, pp. 437-457
dc.relation.uri.none.fl_str_mv http://dx.doi.org/10.1080/09544820701403771
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.local.spa.fl_str_mv Acceso abierto
rights_invalid_str_mv Acceso abierto
http://purl.org/coar/access_right/c_abf2
dc.format.eng.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Taylor & Francis
institution Universidad EAFIT
bitstream.url.fl_str_mv https://repository.eafit.edu.co/bitstreams/7d4afa65-1ff0-48e0-b54d-cd9c94e26099/download
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spelling 2016-11-18T22:23:37Z2007-102016-11-18T22:23:37Z0954-4828http://hdl.handle.net/10784/968910.1080/09544820701403771Surface reconstruction from noisy point samples must take into consideration the stochastic nature of the sample -- In other words, geometric algorithms reconstructing the surface or curve should not insist in following in a literal way each sampled point -- Instead, they must interpret the sample as a “point cloud” and try to build the surface as passing through the best possible (in the statistical sense) geometric locus that represents the sample -- This work presents two new methods to find a Piecewise Linear approximation from a Nyquist-compliant stochastic sampling of a quasi-planar C1 curve C(u) : R → R3, whose velocity vector never vanishes -- One of the methods articulates in an entirely new way Principal Component Analysis (statistical) and Voronoi-Delaunay (deterministic) approaches -- It uses these two methods to calculate the best possible tape-shaped polygon covering the planarised point set, and then approximates the manifold by the medial axis of such a polygon -- The other method applies Principal Component Analysis to find a direct Piecewise Linear approximation of C(u) -- A complexity comparison of these two methods is presented along with a qualitative comparison with previously developed ones -- It turns out that the method solely based on Principal Component Analysis is simpler and more robust for non self-intersecting curves -- For self-intersecting curves the Voronoi-Delaunay based Medial Axis approach is more robust, at the price of higher computational complexity -- An application is presented in Integration of meshes originated in range images of an art piece -- Such an application reaches the point of complete reconstruction of a unified meshapplication/pdfengTaylor & FrancisJournal of Engineering Design, Volume 18, Issue 5, pp. 437-457http://dx.doi.org/10.1080/09544820701403771Acceso abiertohttp://purl.org/coar/access_right/c_abf2Principal component and Voronoi skeleton alternatives for curve reconstruction from noisy point setsinfo:eu-repo/semantics/articlearticleinfo:eu-repo/semantics/publishedVersionpublishedVersionArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1GRÁFICOS POR COMPUTADORTOPOLOGÍATopologyComputer graphicsTopologyComputer graphicsTriangulación de DelaunayIngeniería inversaDiagramas de VoronoiReconstrucción superficialReconstrucción 3DUniversidad EAFIT. Departamento de Ingeniería MecánicaRuíz, ÓscarVanegas, CarlosCadavid, CarlosLaboratorio CAD/CAM/CAEJournal of Engineering DesignJournal of Engineering Design185437457LICENSElicense.txtlicense.txttext/plain; charset=utf-82556https://repository.eafit.edu.co/bitstreams/7d4afa65-1ff0-48e0-b54d-cd9c94e26099/download76025f86b095439b7ac65b367055d40cMD51ORIGINALpca_voronoi_skeleton_curve_reconstruction_ruiz.pdfpca_voronoi_skeleton_curve_reconstruction_ruiz.pdfVersión incompletaapplication/pdf1528410https://repository.eafit.edu.co/bitstreams/2dfb4d6d-6303-44ed-b275-db9604b1e255/downloadd3027ba1fea396eb489c13ae13d39168MD5210784/9689oai:repository.eafit.edu.co:10784/96892021-09-03 15:43:54.701open.accesshttps://repository.eafit.edu.coRepositorio Institucional Universidad EAFITrepositorio@eafit.edu.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