An adaptive multiple model approach for fast content-based skin detection in on-line videos
Rehanullah Khan, Julian Stöttinger, Martin Kampel · 2008
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.