计算机科学 ›› 2016, Vol. 43 ›› Issue (Z6): 210-213.doi: 10.11896/j.issn.1002-137X.2016.6A.050

• 模式识别与图像处理 • 上一篇    下一篇

基于计算机视觉的驾驶员低头行为检测

杨晓峰,邓红霞,李海芳   

  1. 山西建筑职业技术学院 榆次030600,太原理工大学 榆次030600,太原理工大学 榆次030600
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受山西省自然科学(青年科技研究)基金(2014021022-5),国家电网公司科技项目(52053015000W)资助

Detection of Driver’s Head-dipping Based on Computer Vision

YANG Xiao-feng, DENG Hong-xia and LI Hai-fang   

  • Online:2018-12-01 Published:2018-12-01

摘要: 在驾驶过程中使用手机会引起驾驶员的注意力分散,为了对这种行为进行监督和提醒(在公共交通中检测更有意义),提出了一种基于脸部特征提取的驾驶员低头行为的检测方法。该方法使用主动型状模型(Active Shape Model,ASM)算法得到脸部特征点,在此基础上通过脸部特征点的位置信息计算出头部姿势描述信息,最后通过SVM将上述信息分类进而得出头部姿势,其可用于判断驾驶员是否在驾驶过程中低头看手机行为,该方法能够有效检测出驾驶员在驾驶过程中低头使用手机的行为。实验结果表明,该方法的平均检出率在94%以上。

关键词: ASM,脸部特征,驾驶,手机,注意力分散

Abstract: In order to monitor and alert the distraction by using a mobile phone during driving,the method based on the facial feature extraction to detect the driver’s head behavior was proposed.This method uses ASM (Active Shape Mo-del) to obtain the facial feature points,calculates the head posture description on the position information of the face feature points,and draws the head posture classified by SVM from the above information finally.Experimental results show that the method can effectively detect the driver’s head-dipping during driving,and the average detection rate is above 94%.

Key words: ASM,Facial feature,Driving,Phone,Distraction

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