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Tsallis Entropy for Geometry Simplification

This paper presents a study and a comparison of the use of different information-theoretic measures for polygonal mesh simplification. Generalized measures from Information Theory such as Havrda–Charvát–Tsallis entropy and mutual information have been applied. These measures have been used in the error metric of a surface simplification algorithm. We demonstrate that these measures are useful for simplifying three-dimensional polygonal meshes. We have also compared these metrics with the error metrics used in a geometry-based method and in an image-driven method. Quantitative results are presented in the comparison using the root-mean-square error (RMSE)

This work was supported by the Spanish Ministry of Science and Innovation (Project TIN2010-21089-C03-03 and TIN2010-21089-C03-01) and Feder Funds, Bancaixa (Project P1.1B2010-08), Generalitat Valenciana (Project PROMETEO/2010/028) and Project 2009-SGR-643 of Generalitat de Catalunya (Catalan Government)

info:eu-repo/grantAgreement/MICINN//TIN2010-21089-C03-01/ES/CONTENIDO DIGITAL PARA JUEGOS SERIOS: CREACION, GESTION, RENDERIZADO E INTERACCION/

MDPI (Multidisciplinary Digital Publishing Institute)

Manager: Ministerio de Ciencia e Innovación (Espanya)
Generalitat de Catalunya. Agència de Gestió d’Ajuts Universitaris i de Recerca
Author: Castelló, Pascual
González, Carlos
Chover, Miguel
Sbert, Mateu
Feixas Feixas, Miquel
Date: 2011
Abstract: This paper presents a study and a comparison of the use of different information-theoretic measures for polygonal mesh simplification. Generalized measures from Information Theory such as Havrda–Charvát–Tsallis entropy and mutual information have been applied. These measures have been used in the error metric of a surface simplification algorithm. We demonstrate that these measures are useful for simplifying three-dimensional polygonal meshes. We have also compared these metrics with the error metrics used in a geometry-based method and in an image-driven method. Quantitative results are presented in the comparison using the root-mean-square error (RMSE)
This work was supported by the Spanish Ministry of Science and Innovation (Project TIN2010-21089-C03-03 and TIN2010-21089-C03-01) and Feder Funds, Bancaixa (Project P1.1B2010-08), Generalitat Valenciana (Project PROMETEO/2010/028) and Project 2009-SGR-643 of Generalitat de Catalunya (Catalan Government)
Format: application/pdf
Document access: http://hdl.handle.net/10256/8567
Language: eng
Publisher: MDPI (Multidisciplinary Digital Publishing Institute)
Collection: info:eu-repo/semantics/altIdentifier/doi/10.3390/e13101805
info:eu-repo/semantics/altIdentifier/eissn/1099-4300
AGAUR/2009-2014/2009 SGR-643
Is part of: info:eu-repo/grantAgreement/MICINN//TIN2010-21089-C03-01/ES/CONTENIDO DIGITAL PARA JUEGOS SERIOS: CREACION, GESTION, RENDERIZADO E INTERACCION/
Rights: Attribution 3.0 Spain
Rights URI: http://creativecommons.org/licenses/by/3.0/es/
Subject: Informació, Teoria de la
Information theory
Entropia (Teoria de la informació)
Entropy (Information theory)
Title: Tsallis Entropy for Geometry Simplification
Type: info:eu-repo/semantics/article
Repository: DUGiDocs

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