Statistical color models with application to skin detection
International Journal of Computer Vision
Does Colorspace Transformation Make Any Difference on Skin Detection?
WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
Skin Color-Based Video Segmentation under Time-Varying Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive learning of an accurate skin-color model
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Skin detection using neighborhood information
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
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Most of the already proposed skin detection approaches are based on the same pixel-wise paradigm, in which each image pixel is individually analyzed. We think that this paradigm should be extended; context information should be incorporated in the skin detection process. Following this idea, in this article is proposed a robust and fast skin detection approach that uses spatial and temporal context. Spatial context implies that the decision about the class (skin or non-skin) of a given pixel considers information about the pixel's neighbors. Temporal context implies that skin detection is carried out considering not only pixel values from the current frame, but also taking into account past frames and general background reference information.