SVDD-Based Illumination Compensation for Face Recognition

  • Sang-Woong Lee
  • Seong-Whan Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)

Abstract

Illumination change is one of most important and difficult problems which prevent from applying face recognition to real applications. For solving this, we propose a method to compensate for different illumination conditions based on SVDD(Support Vector Data Description). In the proposed method, we first consider the SVDD training for the data belonging to the facial images under various illuminations, and model the data region for each illumination as the ball resulting from the SVDD training. Next, we compensate for illumination changes using feature vector projection onto the decision boundary of the SVDD ball. Finally, we obtain the pre-image under the identical illumination with input image. By repeated for each person, we can recognize a person with facial images under same illumination. We also perform the face recognition in order to verify the efficacy of proposed method.

Keywords

Illumination compensation face reconstruction noise support vector data description face recognition 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Sang-Woong Lee
    • 1
  • Seong-Whan Lee
    • 2
  1. 1.The Robotics Institute, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213USA
  2. 2.Center for Artificial Vision Research, Korea University, Anam-dong, Seongbuk-ku, Seoul 136-713Korea

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