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首页> 外文会议>2016 World Conference on Futuristic Trends in Research and Innovation for Social Welfare >Computer vision based gaze tracking for accident prevention
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Computer vision based gaze tracking for accident prevention

机译：基于计算机视觉的凝视跟踪预防事故

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Distracted driving is one of the main causes of vehicle collisions in India. Passively monitoring a driver's activities constitutes the basis of an automobile safety system that can potentially reduce the number of accidents by estimating the driver's focus of attention. Automotive vehicles are increasingly being equipped with accident avoidance and warning systems for avoiding the potential collision with an external object, such as another vehicle or a pedestrian. Upon detecting a potential factor, such systems typically initiate an action to avoid the collision and/or provide a warning to the vehicle operator. In this paper a complete accident avoidance system is proposed by determining the driver's behavior. As the main causes of vehicle accident were related to human factors, they could be labeled in one of the two main driver's distraction categories (Alcohol Consumption, Drowsiness and distracted vision). The aim of the proposed system is to help in analyzing the factors associated with driver's behavior for the development of accident avoidance systems. The main causes of the traffic accidents, discovered in the analysis of the driver behavior with the help of our system, will be used for the development of assistant devices and alarm systems that could help the driver to avoid risky situations. In this project we are implementing two image processing tool to get the facial geometry based eye region detection for eye closure identification, combined tracking and detection of vehicles. Frequencies of eye blinking and eye closure are used as the indication of sleepy and warning sign is then generated for recommendation; (b) outside an ego vehicle, road traffic is also analyzed.
机译：分心驾驶是印度车辆碰撞的主要原因之一。被动监视驾驶员的活动构成了汽车安全系统的基础，该系统可以通过估计驾驶员的注意力来潜在地减少事故的发生。机动车辆越来越多地配备有事故避免和警告系统，以避免与诸如另一辆车辆或行人之类的外部物体的潜在碰撞。在检测到潜在因素时，这样的系统通常启动动作以避免碰撞和/或向车辆操作者提供警告。通过确定驾驶员的行为，本文提出了一个完整的事故避免系统。由于交通事故的主要原因与人为因素有关，因此可以将其标记为两种主要驾驶员的干扰因素之一（酒精消耗，嗜睡和注意力分散）。拟议系统的目的是帮助分析与驾驶员行为相关的因素，以开发事故避免系统。借助我们的系统在对驾驶员行为进行分析时发现的交通事故的主要原因，将用于开发辅助设备和警报系统，以帮助驾驶员避免发生危险情况。在这个项目中，我们正在实施两个图像处理工具，以获取基于面部几何的眼睛区域检测，以进行眼部闭合识别，组合跟踪和车辆检测。眨眼和闭眼的频率用作困倦的指示，然后生成警告信号以进行推荐； （b）在自我车辆之外，还对道路交通进行了分析。

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