Matthias Wimmer and Bernd Radig. Adaptive Skin Color Classificator. In Proceedings of the first International Conference on Graphics, Vision and Image Processing, pages 324–327, ICGST, Cairo, Egypt, December 2005.

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Abstract

A lot of computer vision applications benefit from robust skin color classification. But this is a hard challenge due to the various image conditions like camera settings, illumination, light source, shadows and many more. Furthermore people?s tans and ethnic groups also extend those conditions. In this work we present a parametric skin color classifier that can be adapted to the conditions of each image or image sequence. This is done by evaluating some previously know skin color pixels which are acquired by applying a face detector. This approach can distinguish skin color from very similar color like lip color or eye brow color. Its high speed and high accuracy makes it appropriate for real time applications such as face tracking and mimic recognition.

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