Abstract
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 regions even with variant lighting conditions and poses.
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Wang, D., Ren, J., Jiang, J., Ipson, S.S. (2008). Skin Detection from Different Color Spaces for Model-Based Face Detection. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Contemporary Intelligent Computing Techniques. ICIC 2008. Communications in Computer and Information Science, vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85930-7_62
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DOI: https://doi.org/10.1007/978-3-540-85930-7_62
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85929-1
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