Facial Features Detection by Coefficient Distribution Map

  • Daidi Zhong
  • Irek Defée
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3691)

Abstract

The Images and video are currently predominantly handled in compressed form. Block-based compression standards are by far the most widespread. It is thus important to devise information processing methods operating directly in compressed domain. In this paper we investigate this possibility on the example of simple facial feature extraction method based on the H.264 AC Transformed blocks. According to our experiments, most horizontal information of face images is mainly distributed over some key features. After applying block transform and quantization to the face images, such significant information become compact and obvious. Therefore, by evaluating the energy of the specific coefficients which are representing the horizontal information, we can locate the key features on the face. The approach is tested on FERET database of face images and good results is provided despite its simplicity.

Keywords

Face Image Feature Detection Human Face Quantization Factor FERET Database 
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

  • Daidi Zhong
    • 1
  • Irek Defée
    • 1
  1. 1.Institute of Signal ProcessingTampere University of TechnologyTampereFinland

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