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快速的完备鉴别保局投影人脸识别算法 被引量：2

Fast Complete Discriminant Locality Preserving Projections for Face Recognition
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摘要 提出一种快速的完备鉴别保局投影算法(FCDLPP).FCDLPP算法只需使用一次瘦QR分解就可求得保局类内散布的零空间的鉴别矢量,然后再进行一次广义特征值分解求得保局类内散布的主元空间的鉴别矢量.另外,FCDLPP对零空间的不规则鉴别特征和主元空间的规则鉴别特征进行融合.理论分析和实验结果表明,FCDLPP算法不论在计算复杂度还是识别率上都比完备的鉴别保局投影算法有更好的性能和效果. Fast complete discriminant locality preserving projections （FCDLPP） is proposed. There is only one step of economic QR faetorization for FCDLPP algorithm to obtain the optimal diseriminant vectors in the null space of locality preserving within-class scatter. Then, one step of eigen-decomposition is used to obtain the optimal diseriminant vectors in the principal space of the locality preserving within-class scatter. Besides, FCDLPP fuses the regular diseriminant features in the principal space and irregular discriminant features in the null space. Theoretical analyses and experimental results show that the proposed FCDLPP outperforms complete diseriminant locality preserving projections （CDLPP） on computational speed and recognition rates.
作者 卢桂馥 王勇 金忠
机构地区 南京理工大学计算机科学与技术学院 安徽工程大学计算机与信息学院
出处 《模式识别与人工智能》 EI CSCD 北大核心 2011年第6期804-809,共6页 Pattern Recognition and Artificial Intelligence
基金 国家自然科学基金项目(No.60873151 60632050) 江苏省普通高校研究生科研创新计划项目(No.178)资助
关键词 人脸识别 完备鉴别保局投影(CDLPP) QR分解 Face Recognition, Complete Discriminant Locality Preserving Projections （CDLPP）, QR factorization
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
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参考文献11

  • 1Duda R O, Hart P E, Stork D G. Pattern Classification. 2nd Edi- tion. New York,USA: John Wiley & Sons, 2000.
  • 2Belhumeur P N, Hespanha J P, Kriegman D J. Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection. IEEE Trans on Pattern Analysis and Machine Intelligence, 1997, 19 (7) : 711 -720.
  • 3Chen Lifen, Liao Hongyuan, Ko M T, et al. A New LDA-Based Face Recognition System Which Can Solve the Small Sample Size Problem. Pattern Recognition, 2000, 33 (10) : 1713 - 1726.
  • 4Li Haifeng, Jiang Tao, Zhang Keshu. Efficient and Robust Feature Extraction by Maximum Margin Criterion. IEEE Trans on Neural Networks, 2006, 7 ( l ) : 157 - 165.
  • 5Roweis S T, Saul L K. Nonlinear Dimensionality Reduction by Locally Linear Embedding. Science, 2000, 290 ( 5500 ) : 2323 - 2326.
  • 6He Xiaofei, Yan Shuicheng, Hu Yuxiao, et al. Face Recognition Using Laplacianfaces. 1EEE Trans on Pattern Analysis and Machine Intelligence, 2005, 27 (3) : 328 - 340.
  • 7Yu Weiwei, Teng Xiaolong, Liu Chongqing. Face Recognition Using Discriminant Locality Preserving Projections. Image and Vision Computing, 2006, 24(3 ): 239- 248.
  • 8Yang Liping, Gong Weiguo, Gu Xiaohua, et al. Bagging Null Space Locality Preserving Discriminant Classifiers for Face Recognition. Pattern Recognition, 2009, 42(9) : 1853 -1858.
  • 9杨利平,龚卫国,辜小花,李伟红,杜兴.完备鉴别保局投影人脸识别算法[J].软件学报,2010,21(6):1277-1286. 被引量：34
  • 10Golub G H, van Loan C F. Matrix Computations. 3rd Edition. Baltimore, USA: The Johns Hopkins University Press, 1996.

二级参考文献4

共引文献33

同被引文献36

  • 1施剑,何成林,杜利民.基于USB2.0的麦克风阵列语音数据采集系统设计[J].计算机工程,2006,32(24):216-218. 被引量：3
  • 2The 2009(RT-09)Rich Transcription Meeting RecognitionEvaluation Plan[EB/OL].(2009-10-21).http://nist.gov/speech/tests/rt/2009.
  • 3Togneri R,Alder M,Attikiouzel J.Dimension and Structure ofthe Speech Space[J].Communications,Speech and Vision,1992,139(2):123-127.
  • 4Riemann B.über Die Hypothesen Welche Der Geometrie ZuGrunde Liegen[M].New York,USA:Dover Publications,1854.
  • 5Yu Weiwei,Teng Xiaolong,Liu Chongqing.Face RecognitionUsing Discriminant Locality Preserving Projections[J].Imageand Vision Computing,2006,24(3):239-248.
  • 6Yang Liping,Gong Weiguo,Gua Xiaohua,et al.Null SpaceDiscriminant Locality Preserving Projections for FaceRecognition[J].Neurocomputing,2008,71(16-18):3644-3649.
  • 7Benesty J,Chen Jingdong,Huang Yiteng.Microphone ArraySignal Processing[M].[S.1.]:Springer,2008:192-193.
  • 8Georgiou P G,Kyriakakis C,Tsakalides P.Robust Time DelayEstimation for Sound Source Localization in NoisyEnvironments[C]//Proc.of IEEE ASSP Workshop onApplications of Signal Processing to Audio and Acoustics.New York,USA:[s.n.],1997.
  • 9TURK M A, PENTLAND A P. Face recognition using eigenfaces[C ] //Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Maui: IEEE Computer Society, 1991:586 - 591.
  • 10BELHUMEUR P N ,HESPANHA J P, KRIEGMAN D J. Eigenfaces vs. Fisherface: Recognition using class specific linear projection [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,1997,19(7) :711 -720.

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模式识别与人工智能
2011年 第6期

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