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...
- 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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|
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 |
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bitstream.checksum.fl_str_mv |
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bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 |
repository.name.fl_str_mv |
Repositorio Institucional Universidad EAFIT |
repository.mail.fl_str_mv |
repositorio@eafit.edu.co |
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1814110621455613952 |
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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 |