Classifier Combination for Face Localization in Color Images

  • Rachid Belaroussi
  • Lionel Prevost
  • Maurice Milgram
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)

Abstract

We present a new method dedicated to the localization of faces in color images. It combines a connexionist model (auto-associative network), an ellipse model based on Generalized Hough Transform, a skin color model and an eyes detector that results in two features. A linear combination of the 3 first models is performed to eliminate most of non face regions. A connexionist combination of the four detectors response is performed on the remaining candidates. Given an input image, we compute a kind of probability map on it with a sliding window. The face position is then determined as the location of the absolute maximum over this map. Improvement of baseline detectors localization rates is clearly shown and results are very encouraging.

Keywords

Color Image Gradient Orientation Classifier Combination Face Localization Skin Detector 
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 2005

Authors and Affiliations

  • Rachid Belaroussi
    • 1
  • Lionel Prevost
    • 1
  • Maurice Milgram
    • 1
  1. 1.LISIF Université Pierre et Marie Curie BC252Paris cedex 05France

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