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Fatigue Detection System for the Drivers Using Video Analysis of Facial Expressions

机译:基于面部表情视频分析的驾驶员疲劳检测系统

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Tiredness, and sleeping of the drivers while driving is one of the main causes of traffic accidents. Observations of the drivers to detect tiredness and fatigue is a complex task which includes behavioral and physical elements. Different approaches were made, including computer vision with the ability to track and monitor the drivers behind the wheel without the intervention in the driving. The proposed system can observe the alertness or tiredness of drivers in order to prevent them from sleeping while driving. In this work, a framework is developed to detect the fatigue-ness from tracking the cornea of eyes by focusing on the face of the driver. It utilizes applying image morphological changes like dilution, erosion, image segmentation like background elimination and Circular Hough Transform (CHT) to detect cornea of an eye on the captured images on drivers. Whenever the fatigue is recognized it will buzz an alarm at the system and necessary actions can be taken. It additionally decreases incorrect outcomes of by disposing of low-quality faces that happened to a video sequence because of issues in sensible lighting, head movement, and posture variety.
机译:驾驶员的疲劳和驾驶时的睡眠是交通事故的主要原因之一。观察驾驶员以发现疲劳和疲劳是一项复杂的任务,其中包括行为和身体因素。采取了不同的方法,包括计算机视觉技术,该技术能够跟踪和监视方向盘后方的驾驶员,而无需干预驾驶。所提出的系统可以观察驾驶员的机敏或疲劳,以防止他们在驾驶时睡觉。在这项工作中,开发了一种框架,通过关注驾驶员的面部来跟踪眼睛的角膜,从而检测疲劳程度。它利用图像形态变化(例如稀释,腐蚀,图像分割(例如背景消除)和圆弧变换(CHT))来检测驾驶员在捕获的图像上的眼睛角膜。只要识别出疲劳,就会在系统上发出警报声,并可以采取必要的措施。此外,由于光线,头部运动和姿势变化等问题,通过处理视频序列中出现的低质量面部,它还减少了不正确的结果。

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