基于打哈欠和头部运动的疲劳监测

K. J. Raman, A. Azman, Venosha Arumugam, S. Z. Ibrahim, S. Yogarayan, Mohd Fikri Azli Abdullah, Siti Fatimah Abdul Razak, A. H. Muhamad Amin, Kalaiarasi Sonaimuthu
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引用次数: 6

摘要

驾驶员疲劳是造成交通事故的主要原因之一。打哈欠是驾驶员疲劳的一个重要特征。嘴部几何特征表征驾驶员的状态。因此驾驶员的口腔检测和信息提取就显得尤为重要。本文提出了一种基于嘴部定位和跟踪驾驶员打哈欠的方法,用于检测驾驶员在驾驶环境中的疲劳程度。然后利用轮廓特征对驾驶员的哈欠进行检测,并根据历史位置进行跟踪。最后,通过张大嘴巴时在黑暗区域的嘴巴比例来检测打哈欠。通过该方法,驾驶员嘴部比例的分辨率比单个摄像机高,特征信息更准确。头部运动部分是疲劳的阶段,使用人脸检测本身来检测头部运动。为了清晰地看到驾驶员的疲劳情况,在驾驶环境中最好检测到驾驶员的打哈欠和头部运动活动,因为这为驾驶员疲劳判断提供了更好的依据。
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Fatigue Monitoring Based on Yawning and Head Movement
Driver fatigue is one of the main reasons causing traffic accidents. Yawning is an important character of driver fatigue. Mouth geometric character represents state of driver. So driver's mouth detection and information extraction is especially important. This paper proposes to locate and track driver's yawning based on mouth using camera to detect driver's fatigue in driving environment. Then contour algorithm features to detect driver's yawning and track it according to historical position. At last, yawning is detected by the ratio of mouth in the name of dark region as when he mouth is widely open. Through this method the resolution ratios which are transferred to percentage of driver's mouth is higher than one camera and the feature information to be more accuracy. The head movement is partially a phase where the fatigue would be detected by using face detection itself to detect the head movement. In order to get a clear vision of driver's fatigue, yawning and head movement activity will be the best to detect in a driving environment since it provides a better basis for driver fatigue judging.
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