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基于支持向量机的人脸识别系统的研究 被引量：6

Face recognition based on support vector machines
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摘要 首先利用PCA进行人脸图像特征提取,然后将此特征数据作为分类器的输入数据。采用的分类器是利用所谓"相似性"方法构造的多个二类SVM分类器,为了提高识别正确率,在多个SVM的输出之后又增加了一级神经网络训练器。以ORL人脸库做的实验中得到了很好的识别效果。 At first,this paper make use of PCA to extract the feature information of images,then make the feature data to be the input information of classifier.The classifier is used so called ＂similar to＂ to construct a number of SVM,in order to improve recognition accuracy rate,added a neural network training device.The recognition experiment result show a good performance in ORL face database.
作者 曾阳艳 叶柏龙
机构地区 湖南商学院 湖南大学软件学院
出处 《计算机工程与应用》 CSCD 北大核心 2008年第15期182-184,共3页 Computer Engineering and Applications
关键词 人脸识别 PCA SVM 神经网络 face recogniton,PCA,SVM,neural network
分类号 TP301.6 [自动化与计算机技术—计算机系统结构]
作者简介 E-mail：yangyanzeng1018@163．com曾阳艳（1981-），女，助教，主要研究领域为人工智能、图形图像处理； 叶柏龙（1964-），男，教授，硕导，研究方向：人工智能、软件工程等。
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参考文献11

  • 1Moghaddam B,Pentland A.Probabilistic visual learning for object representation[J].IEEE Trans on Pattern Analysis and Machine Intelligence, 1997,19 (7) : 696-710.
  • 2Rowley H A,Baluja S,Kanade T.Neural network-based face detection[J].IEEE Trans on Pattern Analysis and Machine Intelligence, 1998,20( 1 ) : 23-38.
  • 3Yullie A,HaUinan P,Cohen D.Feature exaction from faces using deformable templates[J].Intemational Journal of Computer Vision, 1992,8(2):99-111.
  • 4Turk M,Pentland A.Eigenfaces for recognition[J].Joumal of Cognitive Neuroscience, 1991,3( 1 ) :71-86.
  • 5Swets D L,Weng J.Discriminant analysis and eigenspace partition tree for face and object recognition from views[C]//Proc of the 2nd Int'l Conf on Automatic Face and Gesture Recognition.Washington:IEEE Computer Society Press,1996:192-197.
  • 6Brunelli R,Poggio T.Hyper B F.Networks for gender classification[C]// Proc of the DARPA Image Understanding Workshop.San Mateo: Morgan Kaufmann, 1992: 311-314.
  • 7Buhmann J,Lades M,Malsburg C.Size and distortion invariant object recognition by hierarchical graph matching[C]//Proc of the Int'l Joint Conf on Neural Networks.San Diego:IEEE Press, 1990:411- 416.
  • 8Vapnik V N.The nature of statistical learning theory[M].New York: Springer-Verlag, 1995.
  • 9Weston J,Watkins C.Multi-class support vector machinesSD-TR- 98-04[R].Royal Holloway University of London, 1998.
  • 10Nello C,John S T.An introduction to support vector machines and other kernel-based learning methods[M].Beijing,China:Machine Press, 2005.

二级参考文献18

  • 1B Moghaddam,A Pentland.Probabilistic visual learning for object representation.IEEE Trans on Pattern Analysis and Machine Intelligence,1997,19(7):696～710
  • 2H-A Rowley,S Baluja,T Kanade.Neural network-based face detection.IEEE Trans on Pattern Analysis and Machine Intelligence,1998,20(1):23～38
  • 3A Yullie,P Hallinan,D Cohen.Feature exaction from faces using deformable templates.International Journal of Computer Vision,1992,8(2):99～111
  • 4M Turk,A Pentland.Eigenfaces for recognition.Journal of Cognitive Neuroscience,1991,3(1):71～86
  • 5D L Swets,J Weng.Discriminant analysis and eigenspace partition tree for face and object recognition from views.In:Proc of the 2nd Int'l Conf on Automatic Face and Gesture Recognition.Washington:IEEE Computer Society Press,1996.192～197
  • 6R Brunelli,T Poggio.HyperBF networks for gender classification.In:Proc of the DARPA Image Understanding Workshop.San Mateo:Morgan Kaufmann,1992.311～314
  • 7J Buhmann,M Lades,C Malsburg.Size and distortion invariant object recognition by hierarchical graph matching.In:Proc of the Int'l Joint Conf on Neural Networks.San Diego:IEEE Press,1990.411～416
  • 8V N Vapnik.The Nature of Statistical Learning Theory.New York:Springer-Verlag,1995
  • 9J Weston,C Watkins.Multi-class support vector machines.Royal Holloway University of London,Tech Rep:CSD-TR-98-04,1998
  • 10G C Feng,P C Yuen.Multi cues eye detection on gray intensity images.Pattern Recognition,2001,34(5):1033～1046

共引文献16

同被引文献44

引证文献6

二级引证文献29

计算机工程与应用
2008年 第15期

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