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Adaptive Representation of Objects Topology Deformations with Growing Neural Gas

  • José García-Rodríguez
  • Francisco Flórez-Revuelta
  • Juan Manuel García-Chamizo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4507)

Abstract

Self-organising neural networks try to preserve the topology of an input space by means of their competitive learning. This capacity has been used, among others, for the representation of objects and their motion. In this work we use a kind of self-organising network, the Growing Neural Gas, to represent deformations in objects along a sequence of images. As a result of an adaptive process the objects are represented by a topology representing graph that constitutes an induced Delaunay triangulation of their shapes. These maps adapt the changes in the objects topology without reset the learning process.

Keywords

topology preservation topology representation self-organising neural networks shape representation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • José García-Rodríguez
    • 1
  • Francisco Flórez-Revuelta
    • 1
  • Juan Manuel García-Chamizo
    • 1
  1. 1.Department of Computer Technology. University of Alicante. Apdo. 99. 03080 AlicanteSpain

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