Convex Coordinates From Lattice Independent Sets for Visual Pattern Recognition

  • Manuel Graña
  • Ivan Villaverde
  • Ramon Moreno
  • Francisco X. Albizuri
Part of the Studies in Computational Intelligence book series (SCI, volume 67)

Summary. One of the key processes in nowadays intelligent systems is feature extraction. It pervades applications from computer vision to bioinformatics and data mining. The purpose of this chapter is to introduce a new feature extraction process based on the detection of extremal points on the cloud of points that represent the high dimensional data sample. These extremal points are assumed to de.ne an approximation to the convex hull covering the data sample points. The features extracted are the coordinates of the data points relative to the extremal points, the convex coordinates. We have experimented this approach in several applications that will be summarized in the chapter.

Keywords

Principal Component Analysis Feature Extraction Ground Truth Mobile Robot Independent Component Analysis 
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 2007

Authors and Affiliations

  • Manuel Graña
    • 1
  • Ivan Villaverde
    • 1
  • Ramon Moreno
    • 1
  • Francisco X. Albizuri
    • 1
  1. 1.Dept Ciencias Comp e Intel ArtifUniversidad del País VascoSan SebastianSpain

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