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by Nicu Sebe, Ira Cohen, Thomas S. Huang, Theo Gevers
http://carol.wins.uva.nl/~nicu/publications/ICPR04.pdf
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Abstract:
The automated detection and tracking of humans in computer vision necessitates improved modeling of the human skin appearance. In this paper we propose a Bayesian network approach for skin detection. We test several classifiers and propose a methodology for incorporating unlabeled data. We apply the semi-supervised approach to skin detection and we show that learning the structure of Bayesian network classifiers enables learning good classifiers with a small labeled set and a large unlabeled set. 1.
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