Opto-Electronic Engineering, Volume. 42, Issue 6, 8(2015)

Discriminant Sparsity Preserving Embedding with Application to Face Recognition

WANG Guoqiang1,*... SHI Nianfeng1 and GUO Xiaobo2 |Show fewer author(s)
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    References(17)

    [1] [1] BELLMAN R. Adaptive Control Processes: A Guided Tour [M]. Princeton: Princeton University Press, 1961: 140-176.

    [2] [2] ZHAO Zhenhua, HAO Xiaohong. Linear Locality Preserving and Discriminating Projection for Face Recognition [J]. Journal of Electronics & Information Technology, 2013, 35(2): 463-467.

    [3] [3] BELHUMEUR P N, HESPANHA J P, KRIEGMAN D J. Eigenfaces vs. Fisherfaces: Recognition using class projection [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence(S0162-8828), 1997, 19(7): 711-720.

    [4] [4] ROWEIS S L, SAUL L. Nonlinear dimensionality reduction by locally linear embedding [J]. Science(S0036-8075), 2000, 290(5500): 2323-2326.

    [5] [5] BELKIN M, NIYOGI P. Laplacian eigenmaps and spectral techniques for embedding and clustering [C]// Neural Information Processing Systems, Vancouver: MIT Press, 2001: 585-591.

    [6] [6] HE Xiaofei, CAI Deng, YAN Shuicheng, et al. Neighborhood Preserving Embedding [C]// Proc. of 10th IEEE Int. Conf. on Computer Vision, Beijing, China, October 17-20, 2005: 1208-1213.

    [7] [7] HE Xiaofei, YAN Shuicheng, HU Yuxiao, et al. Face recognition using laplacianfaces [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence(S0162-8828), 2005, 27(3): 328-340.

    [8] [8] YAN Shuicheng, XU Dong, ZHANG Benyu, et al. Graph Embedding: A General Framework for Dimensionality Reduction [C]// Proceeding of IEEE Comput, Soc. Conf. Computer Vision and Pattern Recognition, San Diego, CA, United states, June 20-25, 2005: 20-25.

    [9] [9] HOU Shudong, SUN Quansen. Sparsity Preserving Canonicial Correlation Analysis with Application in Feature Fusion [J]. Acta Automatica Sinica, 2012, 38(4): 659-665.

    [10] [10] QIAO Lishan, CHEN Songcan, TAN Xiaoyang. Sparsity Preserving Projections with Applications to Face Recognition [J]. Pattern Recognition(S0031-3203), 2010, 43(1): 331-341.

    [11] [11] LOU Songjiang, ZHAO Xiaoming, ZHANG Shiqing. Local sparse representation and discriminant analysis for feature extraction [J]. Journal of Optoelectronics·Laser, 2013, 24(7): 1406-1409.

    [12] [12] GUI Jie, SUN Zhenan, JIA Wei, et al. Discriminant sparse neighborhood preserving embedding for face recognition [J]. Pattern Recognition(S0031-3203), 2012, 45(8): 2884-2893. WeiJia, RongxiangHu, YingkeLei

    [13] [13] LI Haifeng, JIANG Tao, ZHANG Keshu. Efficient and robust feature extraction by maximum margin criterion [J]. IEEE Transactions on Neural Networks(S1045-9227), 2006, 17(1): 157-165.

    [15] [15] CANDES E, ROMBERG J. l1-Magic: recovery of sparse signals via convex programming [EB/OL]. http://www.acm.caltech.edu/l1magic/, 2005.

    [16] [16] YIN Jun, YANG Wankou. Kernel Sparsity Preserving Projections and Its Application to Biometrics [J]. Acta Electronica Sinica, 2013, 41(4): 639-645.

    [17] [17] ZHANG Dawei, ZHU Shan′an. Face recognition based kernel neighborhood preserving discriminant embedding [J]. Journal of Zhejiang University: Engnineering Science, 2011, 45(10): 1842-1847.

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    WANG Guoqiang, SHI Nianfeng, GUO Xiaobo. Discriminant Sparsity Preserving Embedding with Application to Face Recognition[J]. Opto-Electronic Engineering, 2015, 42(6): 8

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    Paper Information

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    Received: Apr. 14, 2014

    Accepted: --

    Published Online: Jul. 10, 2015

    The Author Email: Guoqiang WANG (wgq2211@163.com)

    DOI:10.3969/j.issn.1003-501x.2015.06.002

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