关于司机疲劳监测的人眼检测与跟踪研究

【作者】 陈艳琴；

【导师】 罗大庸；

【作者基本信息】 中南大学 ， 交通信息工程及控制， 2004， 硕士

【摘要】 目前交通事故中相当一部分是由于司机疲劳驾驶所造成的，为减了少此类事故的发生，本文研究通过司机的眼睛状态来判断司机是否处于疲劳状态，重点对司机眼睛的检测与跟踪的算法进行了研究与改进。 本文主要作了以下几个方面的工作： 1．为了提高人眼检测的准确率和速度，本文提出了两种人眼检测方法：基于肤色模型和级联增强分类器法和基于几何特征和级联增强分类器法。前一种方法主要用于彩色图像中人眼的检测，后一种方法主要适用于灰度图像，这两种方法对于人眼的检测效果较以前的算法都有所改善。 2．检测出人眼之后就要进行眼睛的跟踪，本文提出了一种新颖的眼睛跟踪方法：将Kalman滤波和Mean Shift算法相结合的方法。整个跟踪过程分为两个阶段：首先根据上一帧图像中眼睛的位置运用Kalman滤波预测当前图像中眼睛的位置和协方差；然后根据眼睛的亮度分布特征运用Mean Shift迭代算法在估计的邻域内搜索与眼睛模板最相似的目标。此眼睛跟踪方法在实际的光照条件下跟踪效果较好，对于眼睛部分遮挡或者闭合的情况也能够准确地跟踪。 3．构建了眼睛跟踪系统，实现了司机眼睛的实时跟踪。更多还原

【Abstract】 At present some of traffic accidents have taken place because drivers have been in fatigue. In this thesis driver’s fatigue level has been estimated according to his eyes state in order to reduce these traffic accidents. Eye detection and tracking methods of the driver have been studied and improved importantly.In this thesis three facets work have been finished:Firstly, two methods have been proposed in this thesis that have been used to detect and track eyes, and which are superior to former methods in detecting speed and veracity, one of which is based on color-model and boosted cascade of classifies , and the other is based on geometry feature and boosted cascade of classifies. The former is for color images and the latter is for gray images, and both them are superior to former methods in some degree.Secondly, novel eye tracking method has been proposed that has conjoined kalman filter and mean shift , the whole tracking process has been divided into two stages: kalman filter is used to estimate eye position and mean shift is used to correct eye position. This eye tracking method is effective for realistic lighting condition, eye part closure and eye closure.Thirdly, eye tracking system has been constructed and real time eye tracking has been realized.更多还原