基于ASM和眼嘴自动标点的差距化疲劳识别
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The Fatigue Recognition Based on ASM and the Gap of the Eyes and Mouth Automatic Punctuation
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    摘要:

    人的眼睛和嘴巴是面部当中最能表现状态的重要因素,准确有效的提取它们特征的能够应用于多种场合。针对经典弹性图匹配算法中人脸特征点的定位问题,本文中通过手工标定特征点,用可变形状模型(ASM)法对人眼和嘴部定位点训练,然后使能够机器自动标定,通过匹配后计算与正常状态的点的差距,从而对驾驶员驾驶过程中疲劳状态进行检测和警告;仿真实验得出结论表明此法能利用短时间,快速且较为准确的识别疲劳。

    Abstract:

    The eyes and mouth are one of the most important factors to performance status in a face, accurately and effectively extracting their features can be used in a variety of situations. According to elastic chart matching algorithm for classic face feature points in the localization problem, this paper, through the manual calibration points, uses variable shape model (ASM) method to train the human eye and mouth location point training, then let the machine automatically calibrate through calculating the gap between them and the normal points after matching, and provide provides detection and warning to the driver with fatigue during driving . The emulational experiment shows that this method can identify fatigue quickly and more accurate in a short time.

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王筱薇倩,杨会成,费琛,杨惠.基于ASM和眼嘴自动标点的差距化疲劳识别[J].重庆工商大学学报(自然科学版),2013,30(4):39-44
WANG Xiao-weiqian, YANG Hui-cheng, FEI Chen, YANG Hui. The Fatigue Recognition Based on ASM and the Gap of the Eyes and Mouth Automatic Punctuation[J]. Journal of Chongqing Technology and Business University(Natural Science Edition),2013,30(4):39-44

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