发表机构
National Institute of Technology Karnataka（卡纳塔克邦国立理工学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究开发了一种基于眼睛中心跟踪和动态阈值的低成本实时疲劳检测系统，通过摄像头监测眼睛状态并触发警报，以减少因疲劳驾驶导致的事故。
AI 中文摘要
如今，道路上每五起车辆事故中就有一起仅仅是由驾驶员疲劳引起的。疲劳或困倦会显著降低驾驶员的注意力和警觉性，从而增加固有人员失误的风险，导致受伤和死亡。因此，我们的主要动机是——使用基于非侵入式图像处理的警报系统来减少道路事故。在这方面，我们构建了一个通过实时跟踪和监测驾驶员眼睛模式来检测驾驶员疲劳的系统。该独立系统由三个相互连接的组件组成——处理器、摄像头和警报器。在初始面部检测之后，眼睛被定位、提取并持续监测，以基于逐像素方法检查它们是睁开还是闭合。当观察到眼睛闭合一定时间时，即认为检测到疲劳，并相应发出警报以提醒驾驶员，从而防止伤亡。
英文摘要
One in every five vehicle accidents on the road today is caused simply due to driver fatigue. Fatigue or otherwise drowsiness, significantly reduces the concentration and vigilance of the driver thereby increasing the risk of inherent human error leading to injuries and fatalities. Hence, our primary motive being - to reduce road accidents using a non-intrusive image processing based alert system. In this regard, we have built a system that detects driver drowsiness by real time tracking and monitoring the pattern of the driver's eyes. The stand alone system consists of 3 interconnected components - a processor, a camera and an alarm. After initial facial detection, the eyes are located, extracted and continuously monitored to check whether they are open or closed on the basis of a pixel-by-pixel method. When the eyes are seen to be closed for a certain amount of time, drowsiness is said to be detected and an alarm is issued accordingly to alert the driver and hence, prevent a casualty.
Journal refIntelligent Systems Design and Applications. ISDA 2018 2018. Advances in Intelligent Systems and Computing, vol 940. Springer, Cham
DOI：10.1007/978-3-030-16657-1_24
