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Robust Face-Tracking Using Skin Color and Facial Shape

  • Hyung-Soo Lee
  • Daijin Kim
  • Sang-Youn Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2688)

Abstract

This paper proposes a robust face tracking algorithm based on the CONDENSATION algorithm that uses skin color and facial shape as observation measures. Two independent trackers are used for robust tracking: one is tracking for the skin colored region and another is tracking for the facial shape region. The two trackers are coupled by using an importance sampling technique, where the skin color density obtained from the skin color tracker is used as the importance function to generate samples for the shape tracker. The samples of the skin color tracker within the chosen shape region are updated with higher weights. The proposed face tracker shows a robust tracking performance over the skin color based tracker or the facial shape based tracker given the presence of clutter background and/or illumination changes.

Keywords

Skin Color Color Histogram Facial Shape Clutter Background Face Tracking 
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 2003

Authors and Affiliations

  • Hyung-Soo Lee
    • 1
  • Daijin Kim
    • 2
  • Sang-Youn Lee
    • 3
  1. 1.Department of Computer Science and EngineeringPohang University of Science and TechnologyKorea
  2. 2.Department of Computer Science and EngineeringPohang University of Science and TechnologyKorea
  3. 3.Multimedia Technology LaboratoryKorea TelecomSeoulKorea

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