Evaluating approximations generated by the GNG3D method for mesh simplification

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10045/25293
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Campo DCValorIdioma
dc.contributorCriptología y Seguridad Computacionales
dc.contributor.authorNavarro, Pedro R.-
dc.contributor.authorTortosa, Leandro-
dc.contributor.authorVicent, Jose F.-
dc.contributor.authorZamora, Antonio-
dc.contributor.otherUniversidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificiales
dc.date.accessioned2012-11-23T09:20:47Z-
dc.date.available2012-11-23T09:20:47Z-
dc.date.issued2008-
dc.identifier.citationNAVARRO, Pedro, et al. "Evaluating approximations generated by the GNG3D method for mesh simplification". En: Proceedings of the 7th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases (AIKED '08) : Cambridge, UK, February 23-25, 2008. [S.l.] : WSEAS, 2008. ISBN 978-960-6766-41-1, pp. 25-30es
dc.identifier.isbn978-960-6766-41-1-
dc.identifier.urihttp://hdl.handle.net/10045/25293-
dc.description.abstractIn this paper we present different error measurements with the aim to evaluate the quality of the approximations generated by the GNG3D method for mesh simplification. The first phase of this method consists on the execution of the GNG3D algorithm, described in the paper. The primary goal of this phase is to obtain a simplified set of vertices representing the best approximation of the original 3D object. In the reconstruction phase we use the information provided by the optimization algorithm to reconstruct the faces thus obtaining the optimized mesh. The implementation of three error functions, named Eavg, Emax, Esur, permitts us to control the error of the simplified model, as it is shown in the examples studied.es
dc.description.sponsorshipThe research was supported by the University of Alicante, (GV06/018).es
dc.languageenges
dc.publisherWSEASes
dc.rightsCopyright © 2008 WSEASes
dc.subjectSurface simplificationes
dc.subjectMesh reconstructiones
dc.subjectError approximationses
dc.subjectNeural networkses
dc.subjectGrowing neural gases
dc.subjectGrowing cell structureses
dc.subject.otherCiencia de la Computación e Inteligencia Artificiales
dc.titleEvaluating approximations generated by the GNG3D method for mesh simplificationes
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.peerreviewedsies
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
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