Real time drowsiness detection using eye blink monitoring

Amna Rahman, Mehreen Sirshar, Aliya Khan
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引用次数: 71

Abstract

According to analysis reports on road accidents of recent years, it's renowned that the main cause of road accidents resulting in deaths, severe injuries and monetary losses, is due to a drowsy or a sleepy driver. Drowsy state may be caused by lack of sleep, medication, drugs or driving continuously for long time period. An increase rate of roadside accidents caused due to drowsiness during driving indicates a need of a system that detects such state of a driver and alerts him prior to the occurrence of any accident. During the recent years, many researchers have shown interest in drowsiness detection. Their approaches basically monitor either physiological or behavioral characteristics related to the driver or the measures related to the vehicle being used. A literature survey summarizing some of the recent techniques proposed in this area is provided. To deal with this problem we propose an eye blink monitoring algorithm that uses eye feature points to determine the open or closed state of the eye and activate an alarm if the driver is drowsy. Detailed experimental findings are also presented to highlight the strengths and weaknesses of our technique. An accuracy of 94% has been recorded for the proposed methodology.
使用眨眼监测进行实时睡意检测
根据近年来对道路交通事故的分析报告,众所周知,导致死亡、重伤和经济损失的道路交通事故的主要原因是由于昏昏欲睡或昏昏欲睡的司机。困倦状态可能由睡眠不足、药物、毒品或长时间连续驾驶引起。由于驾驶时困倦而导致的路边交通事故的增加表明需要一个系统来检测驾驶员的这种状态,并在发生任何事故之前提醒他。近年来,许多研究人员对睡意检测表现出了兴趣。他们的方法基本上是监测与驾驶员有关的生理或行为特征,或者与所使用的车辆有关的措施。文献综述总结了在这一领域提出的一些最新技术。为了解决这个问题,我们提出了一种眨眼监测算法,该算法使用眼睛特征点来确定眼睛的打开或关闭状态,并在驾驶员昏昏欲睡时激活警报。详细的实验结果也提出了突出我们的技术的优点和缺点。所提出的方法的准确率为94%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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