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首页> 外文会议>Mexican international conference on artificial intelligence >Driver's Drowsiness Detection Through Computer Vision: A Review
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Driver's Drowsiness Detection Through Computer Vision: A Review

机译：通过计算机视觉检测驾驶员的睡意：综述

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Drowsiness and sleepiness of driver is an important cause of road accident on expressways, highways, and motorways. These accidents not only results in economic loss but may also in physical injuries, which could result permanent disability or even death. The aim of this research is to minimize this cause of road accidents. Safe driving requirement is unavoidable and to attain this, driver's drowsiness detection system is to be incorporate in vehicles. Drowsiness detection using vehicle-based, physiological, and behavioral change measurement system is possible with embedded pros and cons. Advancements in the field of image processing and development of faster and cheaper processors direct researches to focus on behavioral change measurement system for drowsiness detection. Computer vision based drowsiness detection is possible by closely monitoring the drowsiness symptoms like eye blinking intervals, yawning, eye closing duration, head position etc. The presented paper deals with merits and demerits of the drowsiness symptoms measurement mechanism and computer vision based drowsiness detection systems. The conclusion of the research is that by designing a hybrid computer vision based drowsy driver detection system dependability achieved. The proposed system is non-intrusive in nature and helpful in attaining safer roads by limiting potential accidental threat due to driver drowsiness.
机译：驾驶员的困倦和困倦是高速公路，高速公路和高速公路上道路交通事故的重要原因。这些事故不仅造成经济损失，还可能造成人身伤害，甚至可能导致永久性残疾甚至死亡。这项研究的目的是使道路交通事故的发生最小化。安全驾驶要求是不可避免的，要达到这个目的，驾驶员的睡意检测系统将被安装在车辆中。使用基于车辆的生理和行为变化测量系统进行睡意检测具有嵌入式优点和缺点。图像处理领域的进步以及更快，更便宜的处理器的发展直接将研究重点放在了用于睡意检测的行为变化测量系统上。通过紧密监视睡意症状，例如眨眼间隔，打哈欠，闭眼时间，头部位置等，可以进行基于计算机视觉的睡意检测。本文研究了睡意症状测量机制和基于计算机视觉的睡意检测系统的优缺点。研究的结论是，通过设计基于混合计算机视觉的昏昏欲睡的驾驶员检测系统，可以实现可靠性。拟议的系统本质上是非侵入性的，并且通过限制由于驾驶员睡意引起的潜在意外威胁，有助于获得更安全的道路。

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