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.
|Name||Communications in Computer and Information Science|
|Conference||Advanced Intelligent Computing Theories and Applications. With Aspects of Contemporary Intelligent Computing Techniques 4th International Conference on Intelligent Computing|
|Period||15/09/08 → 18/09/08|
- skin detection
- face detection
- performance evaluation