Drowsiness Detection and Alertness Using Eye Motion Monitoring

Rabia Asghar, Ahmad Hassan, Naveed Ur Rehman Junejo, Farwa Ikram, Abeera Mahfooz Cheema
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引用次数: 0

Abstract

The driver felt sleepy when they don’t take proper rest while driving on long routes. The restless driving careless mistake could be fatal to driver as well as others’ lives. This issue has been increased to such a level that a system required to avoid accidents and save life. The driver alertness detection can play a significant role to avoid such hazards. The system can identify the drowsiness on the face of driver and can generate an alarm for them to stop or take necessary actions. Eye state analysis is a key step for alertness detection that helps to identify the state of the eye whether it is open or close. In this paper, the method has been proposed for eye state analysis following face and eye detection to detect driver’s alertness. This system has been integrated into a four-steps includes detection of face, detection of eye, analysis of eye state, and decision regarding driver's drowsiness. A warning signal has been buzzed on drowsiness detection to alarm the driver. Simulation results validate that our proposed idea attains high accuracy and low error rate as compared to state-of-art.
利用眼动监测检测睡意和警觉性
司机在长途行驶中,如果没有好好休息,就会感到困倦。不安分的驾驶失误可能对司机和他人的生命都是致命的。这个问题已经增加到一个系统需要避免事故和拯救生命的程度。驾驶员警觉性检测对避免此类危险起着重要的作用。该系统可以识别驾驶员脸上的睡意,并发出警报,让他们停下来或采取必要的行动。眼睛状态分析是警觉性检测的关键步骤,它有助于识别眼睛的状态,无论它是打开还是关闭。本文提出了一种基于人脸和眼睛检测的眼状态分析方法来检测驾驶员的警觉性。该系统分为四个步骤:人脸检测、眼睛检测、眼睛状态分析、驾驶员睡意判断。在睡意检测上,一个警告信号已经嗡嗡作响,以提醒司机。仿真结果表明,与现有方法相比,该方法具有较高的精度和较低的错误率。
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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