Skin Detection: A Bayesian Network Approach

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.

• Type: Conference
• Year: 2004
• Where: ICPR
• Authors: Ira Cohen, Nicu Sebe, Theo Gevers, Thomas S. Huang
• Keywords: Bayesian Network Classifiers, Computer Vision, ICPR 2004, Large Unlabeled Set, Skin Detection