Alvarez, Rafael, Noguera, José, Tortosa, Leandro, Zamora, Antonio
Computational cost of GNG3D algorithm for mesh simplification
ALVAREZ, Rafael, et al. "Computational cost of GNG3D algorithm for mesh simplification". En: Proceedings of the IADIS International Conference Applied Computing 2007 : Salamanca, Spain, 18-20 February 2007. [S.l.] : IADIS, 2007. ISBN 978-972-8924-30-0, pp. 75-82
URI: http://hdl.handle.net/10045/25294
DOI: 
ISSN: 
ISBN: 978-972-8924-30-0
Abstract: 
In this paper we present a study of the computational cost of the GNG3D algorithm for mesh optimization. This algorithm has been implemented taking as a basis a new method which is based on neural networks and consists on two differentiated phases: an optimization phase and a reconstruction phase. The optimization phase is developed applying an optimization algorithm based on the Growing Neural Gas model, which constitutes an unsupervised incremental clustering algorithm. 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 computational cost of both phases is calculated, showing some examples.
Keywords:Mesh simplification, Polygonal reduction, Computational cost, Neural networks
IADIS
info:eu-repo/semantics/conferenceObject