A combined skin model and feature approach for tracking of human faces
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
A study on stronger face recognition utilizing color information
CSECS '10 Proceedings of the 9th WSEAS international conference on Circuits, systems, electronics, control & signal processing
A new face database and evaluation of face recognition techniques
ICS'10 Proceedings of the 14th WSEAS international conference on Systems: part of the 14th WSEAS CSCC multiconference - Volume II
ANN face detection with skin color distribution rules
Machine Graphics & Vision International Journal
Novel adaptive eye detection and tracking for challenging lighting conditions
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
Face detection based on skin color likelihood
Pattern Recognition
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This paper proposes a novel technique for detecting faces in color images using AdaBoost algorithm combined with skin color segmentation.First,skin color model in the YCbCr chrominance space is built to segment the non-skin-color pixels from the image. Then, mathematical morphological operators are used to remove noisy regions and fill holes in the skin-color region, so we can extract candidate human face regions. Finally,these face candidates are scanned by cascade classifier based on AdaBoost for more accurate face detection. This system detects human face in different scales, various poses, different expressions, lighting conditions, and orientation. Experimental results show the proposed system obtains competitive results and improves detection performance substantially.