基于多参数的驾驶员疲劳检测系统
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摘要
疲劳驾驶已经成为威胁驾驶员安全的重要因素。本文设计了一种融合眼睛状态和心跳速率变化的驾驶员疲劳检测系统,分别研究了驾驶员疲劳时眼睛状态和心跳速率的变化规律,改进了已有的疲劳检测算法以适应驾驶环境。由于融合了眼睛检测子系统和心跳速率检测子系统,该系统既减小了光照等环境因素的影响,又克服了心跳速率检测设备有延迟的缺点,具有更好的准确率。实验结果证明该系统具有良好的鲁棒性和实时性。
Fatigue driving has become a vital factor which threats the safety of drivers.This paper designed a driver monitoring system combined both status of eyes and changes in heartbeat rate.It respectively studied the status of eyes and the variation of heartbeat rate when the diver is fatigue and improved the existing fatigue detection algorithms in order to adapt the driving environment.Because of combining both eyes detection subsystem and heartbeat rate detection subsystem,the whole system can not only overcome the effect from environmental factors,such as light condition,but also overcome the shortcoming that heartbeat detection device has delay when detecting and communicating,so this system has a better accuracy.The experimental results suggested that the system has good robustness and real-time.
Fatigue driving has become a vital factor which threats the safety of drivers.This paper designed a driver monitoring system combined both status of eyes and changes in heartbeat rate.It respectively studied the status of eyes and the variation of heartbeat rate when the diver is fatigue and improved the existing fatigue detection algorithms in order to adapt the driving environment.Because of combining both eyes detection subsystem and heartbeat rate detection subsystem,the whole system can not only overcome the effect from environmental factors,such as light condition,but also overcome the shortcoming that heartbeat detection device has delay when detecting and communicating,so this system has a better accuracy.The experimental results suggested that the system has good robustness and real-time.
引文
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[5]成奋华,杨海燕.基于Gabor小波变换的人脸疲劳模式识别[J].计算机应用,2011,31(08):2119-2122.
[6]http://www.zephyr-technology.com/products/hxmbluetooth-heart-rate-monitor/[EB/OL].
[7]郑艳霞.概率在日常生活和工作中的应用[J].赤峰学院学报(自然科学版),2013,29(2):16-18.
[8]梁涛,张志文.基于OpenCV的视频图像人眼跟踪方法的研究[J].科学技术与工程,2013,13(5):1354-1358.
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[11]刘灵,邓小燕,徐颖.汽车驾驶员驾驶疲劳监测方法与装置的研究现状[J].医疗卫生装备,2006,27(12):28-30.
[12]郑培,宋正河,周一鸣.基于PERCLOS的机动车驾驶员驾驶疲劳的识别算法[J].中国农业大学学报,2002,7(2):104-109.
[13]魏小辉.基于人脸面部特征的驾驶员疲劳检测技术研究[D].河北秦皇岛:燕山大学,2010.
[14]Caldwell J.A.,Caldwell J.L.,Schmidt R.M..Alertness Management Strategies for Operational Contexts[J].Sleep Medicine Reviews,2008,12(4):257-273.
[15]张晓龙,江川,骆名剑.ROC分析技术在机器学习中的应用[J].计算机工程与应用,2007,43(4):243-248.
[2]杨海燕,蒋新华,聂作先.驾驶员疲劳检测技术研究综述[J].计算机应用研究,2010,27(5):1621-1624.
[3]Thomas B.J.,Bekiaris E.,Fischer P.,Lal S.,et al.Using EEG Spectral Components to Assess Algorithms for Detecting Fatigue[J].Expert Systems with Applications,2009,36(2):2352-2359.
[4]Yoshihiro N,Roongroj N,Mieko O.Classification of Blink Waveforms Towards the Assessment of Driver's Arousal Level-An Approach for HMM Based Classification from Blinking Video Sequence[C]//Proceedings of the 7th International Conference on Engineering Psychology and Cognitive Ergonomics.New York:Springer,2007:779-786.
[5]成奋华,杨海燕.基于Gabor小波变换的人脸疲劳模式识别[J].计算机应用,2011,31(08):2119-2122.
[6]http://www.zephyr-technology.com/products/hxmbluetooth-heart-rate-monitor/[EB/OL].
[7]郑艳霞.概率在日常生活和工作中的应用[J].赤峰学院学报(自然科学版),2013,29(2):16-18.
[8]梁涛,张志文.基于OpenCV的视频图像人眼跟踪方法的研究[J].科学技术与工程,2013,13(5):1354-1358.
[9]汪明明,林小竹.基于OpenCV人眼定位的人脸检测方法[J].北京石油化工学院学报,2012,20(4):48-53.
[10]张洁.基于人脸图像的性别识别研究[D].哈尔滨:哈尔滨工程大学,2012.
[11]刘灵,邓小燕,徐颖.汽车驾驶员驾驶疲劳监测方法与装置的研究现状[J].医疗卫生装备,2006,27(12):28-30.
[12]郑培,宋正河,周一鸣.基于PERCLOS的机动车驾驶员驾驶疲劳的识别算法[J].中国农业大学学报,2002,7(2):104-109.
[13]魏小辉.基于人脸面部特征的驾驶员疲劳检测技术研究[D].河北秦皇岛:燕山大学,2010.
[14]Caldwell J.A.,Caldwell J.L.,Schmidt R.M..Alertness Management Strategies for Operational Contexts[J].Sleep Medicine Reviews,2008,12(4):257-273.
[15]张晓龙,江川,骆名剑.ROC分析技术在机器学习中的应用[J].计算机工程与应用,2007,43(4):243-248.