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Skin Detection from Different Color Spaces for Model-based Face Detection

Main information
Skin and face detection has many important applications in intelligent human-machine interfaces, reliable video surveillance and visual understanding of human activities. In this paper, we propose an efficient and effective method for frontal-view face detection based on skin detection and knowledge-based modeling. Firstly, skin pixels are modeled by using supervised training, and boundary conditions are then extracted for skin segmentation. Faces are further detected by shape filtering and knowledge-based modeling. Skin results from different color spaces are compared. In addition, experimental results have demonstrated our method robust in successful detection of skin and face re-gions even with variant lighting conditions and poses. 
No referenced Knowhow defined
WP5: Detection, Extraction and Annotation of Knowledge. 
School of Informatics University of Bradford  Jianmin Jiang, Jinchang Ren 
2008-09-12 11:56  Request for more detail


Access and Use Rights
For educational purposes only - if public document.  For educational purposes only - if public document. 


Protection Status
Copyright School of Informatics, University of Bradford.  Patent Protection not sought. 
Licensing Protection not sought.  Utility Model Protection not sought. 
 
Springer CCIS, Vol. 15, ISBN 978-3-540-85929-1, 2008 
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