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Particle Swarm Optimization for Bézier Surface Reconstruction

  • Akemi Gálvez
  • Angel Cobo
  • Jaime Puig-Pey
  • Andrés Iglesias
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5102)

Abstract

This work concerns the issue of surface reconstruction, that is, the generation of a surface from a given cloud of data points. Our approach is based on a metaheuristic algorithm, the so-called Particle Swarm Optimization. The paper describes its application to the case of Bézier surface reconstruction, for which the problem of obtaining a suitable parameterization of the data points has to be properly addressed. A simple but illustrative example is used to discuss the performance of the proposed method. An empirical discussion about the choice of the social and cognitive parameters for the PSO algorithm is also given.

Keywords

Particle Swarm Optimization Particle Swarm Particle Swarm Optimization Algorithm Surface Reconstruction Particle Swarm Optimization Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Akemi Gálvez
    • 1
  • Angel Cobo
    • 1
  • Jaime Puig-Pey
    • 1
  • Andrés Iglesias
    • 1
  1. 1.Department of Applied Mathematics and Computational SciencesUniversity of CantabriaSantanderSpain

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