Face Detection under Particular Environment Based on Skin Color Model and Radial Basis Function Network
2015 IEEE Fifth International Conference on Big Data and Cloud Computing (BDCloud) (2015)
Aug. 26, 2015 to Aug. 28, 2015
The calculation of the closure of human eyes is commonly adopted to detect driver fatigue. In order to realize human eyes closure calculation, correct and rapid detection of human face is accomplished firstly, for the specific environment of cabs, this paper proposes a fast face detection algorithm based on skin color model and radial basis function network, which makes input image carry out RGB and YCbCr color space conversion, then establishes relevant skin model to achieve the coarse positioning of face region, finally, combines radial basis function network to train input image, so that whether it is the skin color is determined according to the training results, and the detection on face is finished. Simulation results show that the algorithm improves the human face correct detection under strong light, laying a foundation for drivers' fatigue driving research.
Face, Image color analysis, Face detection, Skin, Training, Yttrium, Radial basis function networks
C. Dong, X. Wang, T. Lin and L. Mei-cheng, "Face Detection under Particular Environment Based on Skin Color Model and Radial Basis Function Network," 2015 IEEE Fifth International Conference on Big Data and Cloud Computing (BDCloud)(BDCLOUD), Dalian, China, 2015, pp. 256-259.