Evaluating approximations generated by the GNG3D method for mesh simplification

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Title: Evaluating approximations generated by the GNG3D method for mesh simplification
Authors: Navarro, Pedro R. | Tortosa, Leandro | Vicent, Jose F. | Zamora, Antonio
Research Group/s: Criptología y Seguridad Computacional
Center, Department or Service: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial
Keywords: Surface simplification | Mesh reconstruction | Error approximations | Neural networks | Growing neural gas | Growing cell structures
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial
Issue Date: 2008
Publisher: WSEAS
Citation: NAVARRO, 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. 25-30
Abstract: In 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.
Sponsor: The research was supported by the University of Alicante, (GV06/018).
URI: http://hdl.handle.net/10045/25293
ISBN: 978-960-6766-41-1
Language: eng
Type: info:eu-repo/semantics/conferenceObject
Rights: Copyright © 2008 WSEAS
Peer Review: si
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