期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

基于类Haar特征的驾驶者人眼疲劳状态的检测方法研究 被引量：3

Study on the Method for Driver's Eyes Fatigue State Detection Based on Haar-like Feature
下载PDF
导出
摘要 使用摄像头采集视频图像,对输入图像做预处理(图像灰度化、中值滤波等);通过学习训练的方法构造基于类Haar特征的层叠式分类器,利用基于类Haar特征的层叠式分类器从输入图像中直接定位人眼;把人眼部分的图像截取出来,二值化人眼图像;然后计算二值化图像中垂直方向上瞳孔的宽度大小,从而判断眼睛的状态;最后通过多次的捕捉,计算眼睛闭合的频率来得出其疲劳状态。试验验证了上述算法的有效性。 With help of Haar-like cascaded classifier designed by Adaboost algorithm and constructed by training method, driver＇s eyes were located by the pretreated input video images. Fatigue states of driver＇s eyes were classified by the frequency of blinking. In order to calculate the frequency, the open degrees of the driver＇ s eyes were calculated first, and the eyes＇ images were transferred into binary images, then the pupil widths on vertical direction of the binary images were calculated to judge the fatigue states of eyes. Experiments proved its validity.
作者 林土胜 陈少珠
机构地区 华南理工大学电信学院
出处 《公路交通科技》 CAS CSCD 北大核心 2008年第7期128-131,共4页 Journal of Highway and Transportation Research and Development
基金 国家自然科学基金项目(60472006)
关键词 交通工程 疲劳检测 类Haar层叠式分类器 眼睛定位 图像处理 traffic engineering fatigue state detection Haar-like cascaded classifier eyes location imageprocessing
分类号 U491.254 [交通运输工程—交通运输规划与管理]
  • 相关文献

参考文献9

  • 1王荣本,郭克友,储江伟,初秀民.适用驾驶员疲劳状态监测的人眼定位方法研究[J].公路交通科技,2003,20(5):111-114. 被引量：48
  • 2TERRILLON J C, SHIRAZI M N, FUKAMACHI H, et al.- Comparative Performance of Different Skin Chrominance Models and Chrominance Spaces for the Automatic Detection of Human Faces in Color Images [ C] //Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition.2000: 54- 61.
  • 3FREUND Y, SCHAPIRE R E.A Decision-theoretic Generalization of On- line Learning and An Application to Boosting [J] . Journal of Computer and System Sciences, 1997, 55 (1): 119- 139.
  • 4KANADE T. Picture Processing System by Computer Complex and Recognition of Human Faces [ D] . Kyoto University, 1973.
  • 5YUILLE A L, COHEN D S. Feature Extraction from Faces Using Deformable Templates [ C] //Proceedings of IEEE Computer Society Conference on CRPR. 1989: 104- 109.
  • 6WAITE J, VINCENT J.A Probabilistic Framework for Neural Network Facial Feature Location [J] . British Telecom Technology Journal, 1992, 10 (3) : 20- 29.
  • 7LAM K M, YAN H. Locating and Extracting the Eye in Human Face Images [J] .Pattern Recognition, 1996, 29 (5): 771 - 779.
  • 8PAPAGEORGIOU C, OREN M, POGGIO T.A General Framework for Object Detection [ C] // In International Conference on Computer Vision. 1998 : 555 - 562.
  • 9VIOLA P, JONES M. Rapid Object Detection Using a Boosted Cascade of Simple Features [ C] // Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Hawaii: 2001: 511-518.

二级参考文献8

  • 1G Chow, X Li.Towards Asystem for Automatic Facial Feature Detection[J] .Pattern Recognition, 1993, 26 (12): 1739- 1755.
  • 2J Dengand, F Lai.Region-based Template Deformation and Masking for Eye-feature Extraction and Description [ J ] .Pattern Recognition,1997, 30 (3): 403-419.
  • 3L Huang, C W Chen.Human Facial Feature Extraction for Face Interpretation and Recognition [J] .Pattern Rocognition, 1992, 25 (12):1435 - 1444.
  • 4T Kanade. Picture Processing System by Computer Complex and Recognition of Human Faces [ M] .PhD thesis, Dept of Information Science,Kyoto University, 1973.
  • 5K Lam, H Yan.Locating and Extracting the Eye in Human Face Images[J] .Pattern Recognition, 1996, 29 (5): 771-779.
  • 6X Xie, R Sudhakar, H Zhuang.On Improving Eye Feature Extraction Using Deformable Templates [ J ] .Pattern Recognition, 1994, 27(6) : 791 - 799.
  • 7Jie Yang, Weier Lu, Alex Waibel.Skin-Color Modeling and Adaptation[R] .USA: School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213.
  • 8Tock D, Craw I.Tracking and Measuring Driverseyes [J] .Real-Time Compute, Vision 1995.

共引文献47

同被引文献33

  • 1赵晓华,边扬,张松岭,王沛荣.基于图像处理技术的交叉口分流向流量检测方法研究[J].公路交通科技,2009(S1):97-101. 被引量：2
  • 2施智平,胡宏,李清勇,史忠植,段禅伦.基于纹理谱描述子的图像检索[J].软件学报,2005,16(6):1039-1045. 被引量：44
  • 3王成儒,吴娅辉.旋转不变广义粗糙度特征结合自适应加权距离在纹理检索中的应用[J].中国图象图形学报,2005,10(6):762-766. 被引量：6
  • 4CHOUBEY S K, RAGHAYAN V V. Generic and Fully Automatic Content-Based Image Retrieval Using Color [Jl .Pattern Recognition Letters, 1997, 18 (11 - 13): 1 233- 1 240.
  • 5SMEULDERS W M, WORRING M, SANTINI S, et al. Content-based Image Retrieval at the End of the Early Years I J] . IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22 (12): 1 349-1 380.
  • 6MANJUNATH B S, MAW Y. Texture Features for Browsing and Retrieval of Image Data [J] . IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996, 18 (8) : 837 - 842.
  • 7OJALA T, PIETIKAINEN M, MAENPAA T. Multiresolution Gray-scale and Rotation Invariant Texture Classification with Local Binary Patterns [ J ] . IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24 (7): 971- 987.
  • 8TAKALA V, AHONEN T, PIETIKAINEN M. Block- based Methods for Image Retrieval Using Local Binary Pattern [ C] // Scandinavian Conference on Image Analysis (SCIA) . Berlin: Springer, 2005, 3 540: 882-891.
  • 9AHONEN T, HADID A, PIETIKAINEN M. Face Recognition with Local Binary Patterns [ C ] // European Conference on Computer Vision (ECCV) .Springer, 2004, 3 021: 469- 481.
  • 10王金昌,陈叶开.ABAQUS土木工程中的应用[M].杭州:浙江大学出版社,2006.

引证文献3

二级引证文献7

公路交通科技
2008年 第7期

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