Skin detection: A bayesian network approach

Nicu Sebe, Ira Cohen, Thomas S Huang, Theo Gevers

Research output: Contribution to journalConference articlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)903-906
Number of pages4
JournalProceedings - International Conference on Pattern Recognition
StatePublished - Dec 17 2004
EventProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
Duration: Aug 23 2004Aug 26 2004

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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