The discretized polyhedra simplification (DPS): a framework for polyhedra simplification based on decomposition schemes

This work discusses simplification algorithms for the generation of a multiresolution family of solid representations from an initial polyhedral solid. We introduce the Discretized Polyhedra Simplification (DPS), a framework for polyhedra simplification using space decomposition models. The DPS is b...

Descripción completa

Detalles Bibliográficos
Autores: Andújar Gran, Carlos, Ayala Vallespi, Dolors, Brunet Crosa, Pere
Tipo de recurso: otro
Fecha de publicación:1999
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/29980
Acceso en línea:http://hdl.handle.net/10261/29980
Access Level:acceso abierto
Palabra clave:Pattern recognition
Computer vision
id ES_e1cb57ea8f4004e75d0966394881d44d
oai_identifier_str oai:digital.csic.es:10261/29980
network_acronym_str ES
network_name_str España
repository_id_str
spelling The discretized polyhedra simplification (DPS): a framework for polyhedra simplification based on decomposition schemesAndújar Gran, CarlosAyala Vallespi, DolorsBrunet Crosa, PerePattern recognitionComputer visionThis work discusses simplification algorithms for the generation of a multiresolution family of solid representations from an initial polyhedral solid. We introduce the Discretized Polyhedra Simplification (DPS), a framework for polyhedra simplification using space decomposition models. The DPS is based on a new error measurement and provides a sound scheme for error-bounded, geometry and topology simplification while preserving the validity of the model. A method following this framework, Direct DPS, is presented and discussed. Direct DPS uses an octree for topology simplification and error control, and generates valid solid representations. Our method is also able to generate approximations which do not interpenetrate the original model, either being completely contained in the input solid or bounding it. Unlike most of the current methods, our algorithm can deal and also produces faces with arbitrary complexity. An extension of the Direct method for appearance preservation, called Hybrid DPS, is also discussed.201020101999info:eu-repo/semantics/otherhttp://purl.org/coar/resource_type/c_18ghinfo:eu-repo/semantics/reporthttp://hdl.handle.net/10261/29980reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglésinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/299802026-05-22T06:33:51Z
dc.title.none.fl_str_mv The discretized polyhedra simplification (DPS): a framework for polyhedra simplification based on decomposition schemes
title The discretized polyhedra simplification (DPS): a framework for polyhedra simplification based on decomposition schemes
spellingShingle The discretized polyhedra simplification (DPS): a framework for polyhedra simplification based on decomposition schemes
Andújar Gran, Carlos
Pattern recognition
Computer vision
title_short The discretized polyhedra simplification (DPS): a framework for polyhedra simplification based on decomposition schemes
title_full The discretized polyhedra simplification (DPS): a framework for polyhedra simplification based on decomposition schemes
title_fullStr The discretized polyhedra simplification (DPS): a framework for polyhedra simplification based on decomposition schemes
title_full_unstemmed The discretized polyhedra simplification (DPS): a framework for polyhedra simplification based on decomposition schemes
title_sort The discretized polyhedra simplification (DPS): a framework for polyhedra simplification based on decomposition schemes
dc.creator.none.fl_str_mv Andújar Gran, Carlos
Ayala Vallespi, Dolors
Brunet Crosa, Pere
author Andújar Gran, Carlos
author_facet Andújar Gran, Carlos
Ayala Vallespi, Dolors
Brunet Crosa, Pere
author_role author
author2 Ayala Vallespi, Dolors
Brunet Crosa, Pere
author2_role author
author
dc.subject.none.fl_str_mv Pattern recognition
Computer vision
topic Pattern recognition
Computer vision
description This work discusses simplification algorithms for the generation of a multiresolution family of solid representations from an initial polyhedral solid. We introduce the Discretized Polyhedra Simplification (DPS), a framework for polyhedra simplification using space decomposition models. The DPS is based on a new error measurement and provides a sound scheme for error-bounded, geometry and topology simplification while preserving the validity of the model. A method following this framework, Direct DPS, is presented and discussed. Direct DPS uses an octree for topology simplification and error control, and generates valid solid representations. Our method is also able to generate approximations which do not interpenetrate the original model, either being completely contained in the input solid or bounding it. Unlike most of the current methods, our algorithm can deal and also produces faces with arbitrary complexity. An extension of the Direct method for appearance preservation, called Hybrid DPS, is also discussed.
publishDate 1999
dc.date.none.fl_str_mv 1999
2010
2010
dc.type.none.fl_str_mv info:eu-repo/semantics/other
http://purl.org/coar/resource_type/c_18gh
dc.type.openaire.fl_str_mv info:eu-repo/semantics/report
format other
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/29980
url http://hdl.handle.net/10261/29980
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869422325598781440
score 15,81155

Similares en LA Referencia