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基于SR-2DLPP的人脸识别 被引量：1

Face recognition based on SR-2DLPP
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摘要 提出的SR-2DLPP(spectral regression-2 dimensional locality preserving projection)算法结合2DLPP和SR,将其应用于人脸识别中,并对时间复杂度进行了分析,可以发现其能有效地表示数据内在固有的流形结构,并且计算复杂度和内存消耗都比较小。 The SR-2DLPP which based on spectral regression and 2DLPP applied to face recognition, and analyzed the time complexity. It made efficient use of both labeled and unlabeled points to discover the intrinsic discriminant structure in the data, and the time complexity and memory cost were small.
作者 孙丽娟 杨丹 张小洪 孙丽莉
机构地区 重庆大学数理学院 重庆大学软件学院 华南理工大学自动化学院
出处 《计算机应用研究》 CSCD 北大核心 2009年第7期2789-2792,共4页 Application Research of Computers
关键词 局部保形投影 二维局部保形投影 谱回归 人脸识别 locality preserving projection two-dimensional locality preserving projection spectral regression face recognition
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献16

  • 1TURK M, PENTLAND A. Eigenfaces for recognition[J]. Journal of Cognitive Neuroscience, 1991,13 ( 1 ) :71- 86.
  • 2BORG I, GROENEN P. Modem multidimensional scaling: theory and application [ M ]. New York : Springer-Verlag, 1997.
  • 3BELHUMEUR P N, HESPANHA J P, KRIGMAN D J. Eigenfaces vs. fisherfaces : recognition using class specific linear projection[ J]. IEEE Trans on Pattem Analysis and Machine Intelligence, 1997, 19(7) : 711-720.
  • 4TENENBAUM J B, De SILVA V, LANGFORD J C. A global geometric framework for nonlinear dimensionality reduction [ J ]. Science, 2000, 290(5500):2319-2323.
  • 5ROWEIS S T, SAUL L K. Nonlinear dimensionality reduction by locally linear embedding[ J ]. Science ,2000,290 (5500) :2323-2326.
  • 6BELKIN M, NIYOGI P. Laplacian eigenmaps for dimensionality reduction and data representation [ J ]. Neural Computations, 2003,15 (6) :1373- 1396.
  • 7GUATTERY S, MILLER G L. Graph embeddings and Laplacian eigenvalues[ J]. SIAM Journal on Matrix Analysis and Application, 2000,21 (3) :703- 723.
  • 8HE Xiao-fei, NIYOGI P. Locality preserving projections[ C]//Proc of Neural Information Processing System. California: MIT Press, 2003 : 153-160.
  • 9HE Xiao-fei, YAN Shui-cheng, HU Yu-xiao, et al. Learning a locality preserving subspace for visual recognition [ C ]//Proc of the 9th IEEE International Conference on Computer Vision. Washington DC: IEEE Computer Society, 2003:385-392.
  • 10YANG Jian,ZHANG D,FRANGI A F,et al. Two-dimensional PCA:a new approach to appearance-based face representation and recognition [ J]. IEEE Trans on Pattem Analysis and Machine Intelligence, 2004,26 ( 1 ) : 131-137.

同被引文献14

  • 1He X F, Niyogi P.Locality preserving projections[C]//Proc Conf Advances in Neural Information Processing Systems, 2003.
  • 2Chen S,Zhao H, Kong M, et al.2D-LPP: A two dimen- sional extension of locality preserving projections[J].Neu- rocomputing, 2007,70: 912-921.
  • 3Ben N, Shiu S C K, Pal S K.Two dimensional Laplacian- faces method for face recognition[J].LNCS RSCTC,2006.
  • 4Zhang Zhiwei, Yang Fan.2DLPP:A novel method for small sample size faces recognition[J].Journal of Optoelectronics. Laser,2008,19(7) :972-975.
  • 5The ORL Face Database, Cambridge, U.K, AT&T(Olivetti) Research Laboratories[EB/OL].[2013-05-05].http ://www.uk. research.att.com/facedatabase.html.
  • 6Yale Univ.Face database[EB/OL]. (2002).http://cvc.yale. edu/projects/yalefaces/yalefaces.html. Jain A K.Fundamentals of digital image processing[M].[S.1.] : Prentice Hall, 2011.
  • 7Cai D, He X, Han J, et al.Orthogonal laplacianfaces for face recognition[J].IEEE Transactions on Image Pro- cessing, 2006,15 ( 11 ) : 3608-3614.
  • 8Feng G, Hu D, Zhang D, et al.An alternative formulation of kernel LPP with application to image recognition[J]. Neurocomputing, 2006,69 : 1733-1738.
  • 9Zhao W,Chellappa R,Phillips P J.Subspace linear dis- criminant analysis for face recognition, Tech Report CAR-TR-914[R].Center for Automation Research, Uni- versity of Maryland, 1999.
  • 10Zhao W,Chellappa R,Phillips P J.Subspace linear dis- criminant analysis for face recognition, Tech Report CAR-TR-914[R].Center for Automation Research, Uni- versity of Maryland, 1999.

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计算机应用研究
2009年 第7期

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