期刊文献+

基于多肤色空间及AdaBoost算法的人脸检测方法 被引量:9

Face detection method based on multi-skin color space and AdaBoost algorithm
在线阅读 下载PDF
导出
摘要 针对复杂背景和可变光照下的彩色图像人脸检测问题,提出一种基于多肤色空间下的肤色分割及Ada-Boost算法的人脸检测方法。首先利用均值滤波、拉普拉斯算子等方法对图像进行增强处理;然后结合YCbCr、YCgCr、YCgCb三种颜色空间下的多肤色空间对图像进行肤色分割,定位出候选的人脸区域;最后对AdaBoost算法的检测过程进行研究验证,检测出人脸并指示。数据显示,该方法在时间、检测率、漏检率等方面都有明显的改进。因此,该方法能较好地处理复杂背景下彩色图像人脸检测的错检、漏检问题,从而提高了检测效率。 Focused on face detection problems of color image under the conditions of the complex background and variable illumination,this paper proposed a human face detection method based on multil-skin color space detection and AdaBoost algorithm.First,it used the methods such as the averaging filtering and Laplacian operator to do the image enhancement,and then,combined the three color space of YCbCr,YCgCr,YCgCb to do skin color segmentation and located the candidate's face area.At last,it used AdaBoost algorithm after improving detection process to test and indicate.Statistics show that it has a better detection efficiency,faster speed and lower rate of false.Therefore,the proposed method can handle the problem of false and missing better on face detection of color image under the complex background,and improve efficiency of face detection.
出处 《计算机应用研究》 CSCD 北大核心 2012年第6期2368-2370,共3页 Application Research of Computers
基金 国家自然科学基金资助项目(61100114) 国家教育部科学技术研究重点资助项目(210184) 重庆市教委科学技术研究资助项目(kJ100519) 重庆邮电大学自然科学基金资助项目(A2009-34)
关键词 YCBCR颜色空间 YCGCR颜色空间 YCgCb颜色空间 窗口合并 AdaBoost级联分类器 人脸检测 YCbCr color space YCgCr color space YCgCb color space frames merging AdaBoost cascade classifier face detection
  • 相关文献

参考文献8

  • 1梁路宏,艾海舟,徐光祐,张钹.人脸检测研究综述[J].计算机学报,2002,25(5):449-458. 被引量:355
  • 2FREUND Y. Boosting a weak learning algorithm by majority[ J]. Information and Computation, 1995,121 ( 2 ) :256-285.
  • 3VIOLA P,JONES M. Rapid object detection using a boosted cascade of simple feature[ C ]//Proc of IEEE Conference on Computer Vision and Pattern Recognition. 2001:511-518.
  • 4冈萨雷斯.数字图像处理[M].阮秋琦,等译.3版.北京:电子工业出版社.2007:93-105.
  • 5JOSE M,MIGUEL A,JUAN A,et al. Detecting skin in face recognition system:a colour space study [ J ].Digital Signal Processing, 2010,20(3 ) :806-823.
  • 6张争珍,石跃祥.YCgCr颜色空间的肤色聚类人脸检测法[J].计算机工程与应用,2009,45(22):163-165. 被引量:35
  • 7VIOLA P, JONES M. Robust real-time object detection[ J]. International Journal of Computer Vision, 2004,57 ( 2 ) : 137-154.
  • 8DEMIRKIR C ,SANKUR B. Face detection using look-up table based Gentle Adaboost [ C ]//LNCS, vol 3546. 2005:339-345.

二级参考文献64

  • 1江珂,王玲.运用肤色信息和模板匹配的彩色人脸检测[J].中国测试技术,2006,32(1):53-55. 被引量:6
  • 2Craw I, Ellis H, Lishman J. Automatic extraction of face features. Pattern Recognition Letters, 1987, 5(2):183-187
  • 3Yang G Z, Huang T S. Human face detection in a complex background. Pattern Recognition, 1994, 27(1):53-63
  • 4Dai Y, Nakano Y. Face-texture model based on SGLD and its application in face detection in a color scene. Pattern Recognition, 1996, 29(6):1007-1017
  • 5Kouzani A Z, He F, Sammut K. Commonsense knowledge-based face detection. In: Proc Conference on Intelligent Engineering Systems, Budapast, Hungary, 1997. 215-220
  • 6Garcia C, Tziritas G. Face detection using quantized skin color regions merging and wavelet packet analysis. IEEE Trans Multimedia, 1999, 1(3):264-277
  • 7Sun Q B, Huang W M, Wu J K. Face detection based on color and local symmetry information. In: Proc Conference Automatic Face and Gesture Recognition, Nara, Japan, 1998. 130-135
  • 8Kim S H, Kim H G. Face detection using multi-modal information. In: Proc Conference on Automatic Face and Gesture Recognition, Grenoble, France, 2000. 70-76
  • 9Govindaraju V, Srihari S N, Sher D B. A computational model for face location. In: Proc IEEE Conference on Computer Vision, Osaka, Japan, 1990. 718-721
  • 10Lam K M. A fast approach for detecting human faces in a complex background. In: Proc Symposium on Circuits and Systems, Monterey, 1998, 4:85-88

共引文献384

同被引文献87

  • 1王文宁,李慧娟,师磊.一种基于颜色和形状特征的人脸检测方法[J].计算机系统应用,2008,17(7):58-61. 被引量:5
  • 2李刚,邱尚斌,林凌,曾锐利.基于背景差法和帧间差法的运动目标检测方法[J].仪器仪表学报,2006,27(8):961-964. 被引量:113
  • 3丘维声.解析几何[M].北京:北京大学出版社,1999.200.
  • 4Kasturi R, Goldgof D, Soundararajan P, et al. Framework for performance evaluation of face, text, and vehicle detection and tracking in video:data metrics and protocol[J]. IEEE Transac- tions on Pattern Analysis and Machine Intelligence, 2009, 31 (2) ,319-336.
  • 5陈煜.人脸检测跟踪算法的研究与基于DaVinci的人脸检测系统实现[D].上海:上海交通大学,2009.
  • 6Dockstader S L, Imennov N S, Tekalp A M. Markov-based fail ure prediction for human motion analysis[J]. Computer Vision 2003,Proceedings. Ninth IEEE International Canference, 2003 2:1283-1288.
  • 7Omaniciu D C, Ramesh V, Meer P. Kernel-based object track- ing[J]. IEEE Transactions on Pattern and Analysis and Machine Intelligence, 2003,25(5) :564-577.
  • 8Voila P, Jones M. Rapid object detection using a boosted cas cade of simple features[J]. Computer Vision and Pattern Recog nition,2001. CVPR 2001. Proceedings of the 2001 IEEE Corn puter Society Conference. I, 2001,1 : 511-518.
  • 9Barnich O, Van Droogenbroeek M. ViBe: A universal back- ground subtraction algorithm for video sequences [J]. IEEE Transactions on Image Processing, 2011,20(6) : 1709-1724.
  • 10YANG M, KRIEGMAN D J, AHUJA N. Detecting faces in images: a survey [ J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24( 1 ) : 34 -58.

引证文献9

二级引证文献28

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