计算机应用与软件2013，Vol.30Issue(3)：25-27,54,4.DOI:10.3969/j.issn.1000-386x.2013.03.007
基于眼睛和嘴巴状态的驾驶员疲劳检测算法
DRIVER FATIGUE DETECTION ALGORITHM BASED ON THE STATES OF EYES AND MOUTH
摘要
Abstract
Aiming at the problems of train drivers fatigue detection, we propose a fatigue detection algorithm which is based on the states of eyes and mouth of drivers. First, the improved AdaBoost algorithm is used to accurately locate the face area of drivers, then the human eyes are located through template matching, and the mouth is positioned according to the geometrical characteristics of human face. Finally the PERCLOS parameters of each frame of the image and the frequency of mouth movements are calculated, the relationship of double parameters within the unit time and the corresponding threshold is counted as the base of driving fatigue judgement. Experimental results show that to integrate the information of eyes and mouth reduces the probability of misjudgement and judgement leaks compared with the detection algorithm using single parameter under the condition of normal light. The method has good precision and robustness.关键词
Adaboost/PERCLORS/模板匹配/数据融合/疲劳检测Key words
Adaboost / PERCLORS/ Template matching / Data fusion / Fatigue detection分类
信息技术与安全科学引用本文复制引用
邬敏杰,穆平安,张彩艳..基于眼睛和嘴巴状态的驾驶员疲劳检测算法[J].计算机应用与软件,2013,30(3):25-27,54,4.基金项目
国家自然科学基金项目(51075280) （51075280）
上海市教育委员会重点学科项目(J50505). （J50505）
