Interpolation centers' selection using hierarchical curvature-based clustering

It is widely known that some fields related to graphic applications require realistic and full detailed three-dimensional models. Technologies for this kind of applications exist. However, in some cases, laser scanner get complex models composed of million of points, making its computationally diffi...

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Autores:
Rodríguez, Juan C.
Del Portillo Z, Diego
Sánchez Torres, Germán
Tipo de recurso:
Article of journal
Fecha de publicación:
2010
Institución:
Universidad de Medellín
Repositorio:
Repositorio UDEM
Idioma:
spa
OAI Identifier:
oai:repository.udem.edu.co:11407/864
Acceso en línea:
http://hdl.handle.net/11407/864
Palabra clave:
Clustering
point simplification
range data
interpolation
numerical integration
curvature
Rights
License
http://creativecommons.org/licenses/by-nc-sa/4.0/
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spelling Rodríguez, Juan C.Del Portillo Z, DiegoSánchez Torres, Germán2014-10-22T23:26:07Z2014-10-22T23:26:07Z2010-12-311692-3324http://hdl.handle.net/11407/8642248-4094reponame:Repositorio Institucional Universidad de Medellínrepourl:https://repository.udem.edu.co/instname:Universidad de MedellínIt is widely known that some fields related to graphic applications require realistic and full detailed three-dimensional models. Technologies for this kind of applications exist. However, in some cases, laser scanner get complex models composed of million of points, making its computationally difficult. In these cases, it is desirable to obtain a reduced set of these samples to reconstruct the function's surface. An appropriate reduction approach with a non-significant loss of accuracy in the reconstructed function with a good balance of computational load is usually a non-trivial problem. In this article, a hierarchical clustering based method by the selection of center using the geometric distribution and curvature estimation of the samples in the 3D space is described.Electrónicoapplication/pdfspaUniversidad de MedellínFacultad de IngenieríasMedellínhttp://revistas.udem.edu.co/index.php/ingenierias/article/view/170Revista Ingenierías Universidad de Medellínhttp://creativecommons.org/licenses/by-nc-sa/4.0/Attribution-NonCommercial-ShareAlike 4.0 Internationalhttp://purl.org/coar/access_right/c_abf2Revista Ingenierías Universidad de Medellín; Vol. 9, núm. 17 (2010); 131-1382248-40941692-3324Clusteringpoint simplificationrange datainterpolationnumerical integrationcurvatureInterpolation centers' selection using hierarchical curvature-based clusteringArticlehttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Artículo científicoinfo:eu-repo/semantics/articlehttp://purl.org/coar/version/c_970fb48d4fbd8a85Comunidad Universidad de MedellínTHUMBNAILInterpolation centers' selection using hierarchical curvature-based clustering.pdf.jpgInterpolation centers' selection using hierarchical curvature-based clustering.pdf.jpgIM Thumbnailimage/jpeg6806http://repository.udem.edu.co/bitstream/11407/864/3/Interpolation%20centers%27%20selection%20using%20hierarchical%20curvature-based%20clustering.pdf.jpg82de606b43d84bf52dddb24eeed4dcd0MD53ORIGINALArticulo.htmltext/html574http://repository.udem.edu.co/bitstream/11407/864/1/Articulo.html5a8b9ee2e9ccb20eab0589bfa4d595d4MD51Interpolation centers' selection using hierarchical curvature-based clustering.pdfInterpolation centers' selection using hierarchical curvature-based clustering.pdfTexto completoapplication/pdf639593http://repository.udem.edu.co/bitstream/11407/864/2/Interpolation%20centers%27%20selection%20using%20hierarchical%20curvature-based%20clustering.pdf20e8321bf79ded1edbb603a8837126d3MD5211407/864oai:repository.udem.edu.co:11407/8642021-05-14 14:13:43.584Repositorio Institucional Universidad de Medellinrepositorio@udem.edu.co
dc.title.spa.fl_str_mv Interpolation centers' selection using hierarchical curvature-based clustering
title Interpolation centers' selection using hierarchical curvature-based clustering
spellingShingle Interpolation centers' selection using hierarchical curvature-based clustering
Clustering
point simplification
range data
interpolation
numerical integration
curvature
title_short Interpolation centers' selection using hierarchical curvature-based clustering
title_full Interpolation centers' selection using hierarchical curvature-based clustering
title_fullStr Interpolation centers' selection using hierarchical curvature-based clustering
title_full_unstemmed Interpolation centers' selection using hierarchical curvature-based clustering
title_sort Interpolation centers' selection using hierarchical curvature-based clustering
dc.creator.fl_str_mv Rodríguez, Juan C.
Del Portillo Z, Diego
Sánchez Torres, Germán
dc.contributor.author.none.fl_str_mv Rodríguez, Juan C.
Del Portillo Z, Diego
Sánchez Torres, Germán
dc.subject.spa.fl_str_mv Clustering
point simplification
range data
interpolation
numerical integration
curvature
topic Clustering
point simplification
range data
interpolation
numerical integration
curvature
description It is widely known that some fields related to graphic applications require realistic and full detailed three-dimensional models. Technologies for this kind of applications exist. However, in some cases, laser scanner get complex models composed of million of points, making its computationally difficult. In these cases, it is desirable to obtain a reduced set of these samples to reconstruct the function's surface. An appropriate reduction approach with a non-significant loss of accuracy in the reconstructed function with a good balance of computational load is usually a non-trivial problem. In this article, a hierarchical clustering based method by the selection of center using the geometric distribution and curvature estimation of the samples in the 3D space is described.
publishDate 2010
dc.date.created.none.fl_str_mv 2010-12-31
dc.date.accessioned.spa.fl_str_mv 2014-10-22T23:26:07Z
dc.date.available.spa.fl_str_mv 2014-10-22T23:26:07Z
dc.type.eng.fl_str_mv Article
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dc.identifier.eissn.none.fl_str_mv 2248-4094
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dc.relation.uri.none.fl_str_mv http://revistas.udem.edu.co/index.php/ingenierias/article/view/170
dc.relation.ispartofjournal.spa.fl_str_mv Revista Ingenierías Universidad de Medellín
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dc.rights.uri.*.fl_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rights.creativecommons.*.fl_str_mv Attribution-NonCommercial-ShareAlike 4.0 International
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International
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dc.format.medium.spa.fl_str_mv Electrónico
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad de Medellín
dc.publisher.faculty.spa.fl_str_mv Facultad de Ingenierías
dc.publisher.place.spa.fl_str_mv Medellín
dc.source.spa.fl_str_mv Revista Ingenierías Universidad de Medellín; Vol. 9, núm. 17 (2010); 131-138
2248-4094
1692-3324
institution Universidad de Medellín
bitstream.url.fl_str_mv http://repository.udem.edu.co/bitstream/11407/864/3/Interpolation%20centers%27%20selection%20using%20hierarchical%20curvature-based%20clustering.pdf.jpg
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