An adaptive multiple model approach for fast content-based skin detection in on-line videos

  • Authors:
  • Rehanullah Khan;Julian Stöttinger;Martin Kampel

  • Affiliations:
  • Vienna University of Technology, Vienna, Austria;Vienna University of Technology, Vienna, Austria;Vienna University of Technology, Vienna, Austria

  • Venue:
  • AREA '08 Proceedings of the 1st ACM workshop on Analysis and retrieval of events/actions and workflows in video streams
  • Year:
  • 2008

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Abstract

We propose a straightforward skin detection method for online videos. To overcome varying illumination circumstances and a variety of skin colors, we introduce a multiple model approach which can be carried out independently per model. The color models are initiated by skin detection based on face detection and adapted in real time. Our approach outperforms static approaches both in precision and runtime. If we detect a face in a scene, the number of false positives can be diminished significantly. Evaluation is carried out on publicly available on-line videos showing that adaptive multiple model outperforms static methods in classification precision and suppression of false positives.