期刊文献+

视频图像中的视觉疲劳实时检测方法研究 被引量:2

Real time detection method of visual fatigue in video image
在线阅读 下载PDF
导出
摘要 提出一种新的适用于驾驶中视觉疲劳实时检测的人脸定位及眼睛状态分析算法。采用差分法快速找到视频图像中的目标运动区域,结合YCbCr色彩空间进行肤色分割定位人脸。对脸部区域进行灰度积分投影并结合Hough变换检测眼睑。对检测到的眼睑进行数据分析,得到眼睛开闭情况,结合眨眼分析,获得EOD值来判断驾驶员是否疲劳。实验结果显示该方法能在复杂背景下快速定位人脸,检测到眼睛睁开时的EOD值,满足视觉疲劳检测的实时需要。 It puts forward a new visual fatigue analysis algorithm which is applicable to detect face location and eyes state in driving at real time. The differential method is quickly used to find the target area of video. Face is positioned by skin color segmentation combining YCbCr color space. The eyelid is detected by using the gray integral projection and Hough transform in the area of face. The detected data of eyelid is analyzed, and the condition of eyes is got. Value of EOD is to judge whether the driver is fatigue combined with blink analysis. The experimental result shows that the method can locate face quickly in complex background. The value of EOD is detected when the eyes open, and real-time test of visual fatigue is improved.
作者 兰婷 普杰信
出处 《计算机工程与应用》 CSCD 2012年第35期147-150,共4页 Computer Engineering and Applications
基金 河南省科技攻关计划(No.092102210293) 河南省基础与前沿计划(No.102300410113)
关键词 疲劳驾驶 视频 肤色分割 HOUGH变换 眨眼周期 driving fatigue video skin color segmentation Hough transform blink cycle
  • 相关文献

参考文献9

二级参考文献62

共引文献172

同被引文献19

  • 1王磊,吴晓娟,俞梦孙.驾驶疲劳/瞌睡检测方法的研究进展[J].生物医学工程学杂志,2007,24(1):245-248. 被引量:35
  • 2Li Liling, Xie Mei, Dong Huazhi. A method of driving fatigue detection based on eye location [C] //IEEE ard International Conference on Communication Software and Networks, 2011: 480-484.
  • 3Coetzer R C, Hancke G P. Eye detection for real-time vehicle driver fatigue monitoring system [C]//IEEE Intelligent Vehicles Symposium, 2011: 66-71.
  • 4Horak K. Fatigue features based on eye tracking for driver inattention system [C]//34th International Conference on Telecommunications and Signal Processing, 2011: 593-597.
  • 5Jun Nishimura, Tadahiro, Kuroda. Recognition using haar-like feature and cascaded classifier [J]. Sensors Journal, IEEE, 2010, 10 (5): 942-951.
  • 6Ivan Culjak, David Abram, TomislavPribanic, et al. A brief introduction to OpenCV [C]//Proceedings of the 35th International Convention, 2012: 1725-1730.
  • 7Viola P, Jones M. Rapid Object Detection Using aboosted Caseade of SimpIe Features[J]. IEEE Corn puter Society Con{erence on ComPuter Vision and Pat- ten recognition, 2001,24(1) : 511-518.
  • 8Rainer Lienhart, Joehen Maydt. An Extended Set of Haar-like Features for Rapid Object Detection [J]. IEEE ICIP, 2008,24 (1) .. 28-56.
  • 9Paul Viola, Miehael Jones. Robust Real-Time Face De teetionJ]. International Journal of ComPuter Vision, 2004,57(2) : 137-154.
  • 10于仕琪.OpenCV概述[z].http://wiki.opencv.org.cn/indemphp/OenCV概述,201004-16,34(2):8587.YUShiqi.Abstract.OpenCVOverview[Z].http://wiki.opencv.org.cn/index.php/OpenCVoverview,2010-04-16,34(2):8587.

引证文献2

二级引证文献7

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部