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Face Detection under Particular Environment Based on Skin Color Model and Radial Basis Function Network

机译:基于肤色模型和径向基函数网络的特殊环境下人脸检测

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摘要

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.
机译:通常采用人眼闭合的计算来检测驾驶员疲劳。为了实现人眼闭眼的计算,首先要对人脸进行正确,快速的检测,针对驾驶室的特定环境,提出一种基于肤色模型和径向基函数网络的快速人脸检测算法,使输入图像成为可能。进行RGB和YCbCr颜色空间转换,然后建立相关的皮肤模型以实现人脸区域的粗定位,最后,结合径向基函数网络对输入图像进行训练,从而根据训练结果确定是否为皮肤颜色,面部检测完成。仿真结果表明,该算法提高了强光下人脸的正确检测能力,为驾驶员疲劳驾驶的研究奠定了基础。

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