Independent Component Analysis and Support Vector Machine for Face Feature Extraction

  • Gianluca Antonini
  • Vlad Popovici
  • Jean-Philippe Thiran
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2688)

Abstract

We propose Independent Component Analysis representation and Support Vector Machine classification to extract facial features in a face detection/localization context. The goal is to find a better space where project the data in order to build ten different face-feature classi fiers that are robust to illumination variations and bad environment conditions. The method was tested on the BANCA database, in different scenarios: controlled conditions, degraded conditions and adverse conditions.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Gianluca Antonini
    • 1
  • Vlad Popovici
    • 1
  • Jean-Philippe Thiran
    • 1
  1. 1.Signal Processing Institute Swiss Federal Institute of Technology LausanneLausanneSwitzerland

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