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http://dx.doi.org/10.3837/tiis.2015.11.014

Local Similarity based Discriminant Analysis for Face Recognition  

Xiang, Xinguang (School of Computer Science and Engineering, Nanjing University of Science of Technology)
Liu, Fan (College of Computer and Information, Hohai University)
Bi, Ye (School of Computer Science and Engineering, Nanjing University of Science of Technology)
Wang, Yanfang (College of Computer and Information, Hohai University)
Tang, Jinhui (School of Computer Science and Engineering, Nanjing University of Science of Technology)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.9, no.11, 2015 , pp. 4502-4518 More about this Journal
Abstract
Fisher linear discriminant analysis (LDA) is one of the most popular projection techniques for feature extraction and has been widely applied in face recognition. However, it cannot be used when encountering the single sample per person problem (SSPP) because the intra-class variations cannot be evaluated. In this paper, we propose a novel method called local similarity based linear discriminant analysis (LS_LDA) to solve this problem. Motivated by the "divide-conquer" strategy, we first divide the face into local blocks, and classify each local block, and then integrate all the classification results to make final decision. To make LDA feasible for SSPP problem, we further divide each block into overlapped patches and assume that these patches are from the same class. To improve the robustness of LS_LDA to outliers, we further propose local similarity based median discriminant analysis (LS_MDA), which uses class median vector to estimate the class population mean in LDA modeling. Experimental results on three popular databases show that our methods not only generalize well SSPP problem but also have strong robustness to expression, illumination, occlusion and time variation.
Keywords
Face recognition; single sample per person problem; linear discriminative analysis; local similarity;
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1 M. Yang, Luc Van, and L. Zhang. "Sparse variation dictionary learning for face recognition with a single training sample per person," in Proc. of IEEE International Conference on Computer Vision, pp. 689-696, December 3-6, 2013. Article (CrossRef Link)
2 W. Deng, J. Hu, X. Zhou, and J. Guo, “Equidistant prototypes embedding for single sample based face recognition with generic learning and incremental learning,” Pattern Recognition, vol. 47, no. 12, pp. 3738–3749, 2014. Article (CrossRef Link)   DOI
3 Weihong Deng, Jiani Hu, and Jun Guo, “Extended SRC: Undersampled Face Recognition via Intraclass Variant Dictionary,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, no. 9, pp. 1864–1870, 2012. Article (CrossRef Link)   DOI
4 Jun Yu, Meng Wang, and Dacheng Tao, “Semisupervised Multiview Distance Metric Learning for Cartoon Synthesis,” IEEE Transaction on Image Processing, vol. 21, no. 11, pp. 4636–4648, 2012. Article (CrossRef Link)   DOI
5 P. Zhu, et al. "Local Generic Representation for Face Recognition with Single Sample per Person," in Proc. of Asian Conference on Computer Vision, pp. 34-50, November 1-5, 2014. Article (CrossRef Link)
6 Yu, R. Hong, M. Wang, and J. You, “Image clustering based on sparse patch alignment framework,” Pattern Recognition, vol. 47, no. 11, pp. 3512–3519, 2014. Article (CrossRef Link)   DOI
7 J. Yu, D. Tao, M. Wang, and Y. Rui, “Learning to Rank Using User Clicks and Visual Features for Image Retrieval,” IEEE Transactions on Cybernetics, vol. 45, no. 4, pp. 767–779, 2015. Article (CrossRef Link)   DOI
8 Jun Yu, Dacheng Tao, and Meng Wang, “Adaptive Hypergraph Learning and its Application in Image Classification,” IEEE Transaction on Image Processing, vol. 21, no. 7, pp. 3262–3272, 2012. Article (CrossRef Link)   DOI
9 T. Sim, S. Baker, and M. Bsat, “The CMU pose, illumination, and expression database,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 12, pp. 1615-1618, 2003. Article (CrossRef Link)   DOI
10 J. Yang, J. Yang, D. Zhang, “Median Fisher Discriminator: a robust feature extraction method with applications to biometrics,” Frontiers of Computer Science in China, vol. 2, no. 3, pp. 295–305, 2008. Article (CrossRef Link)   DOI
11 Matthew. Turk, Alex Pentland, “Eigenfaces for recognition,” Journal of cognitive neuroscience, vol. 3, no. 1, pp. 71-86, 1991. Article (CrossRef Link)   DOI
12 S.C. Chen, Y.L. Zhu., “Subpattern-based principle component analysis,” Pattern Recognition, vol. 37, no. 1, pp. 1081-1083, 2004. Article (CrossRef Link)   DOI
13 F. Liu, Y. Bi, Y. Cui, Z. Tang, "Local Similarity based Linear Discriminant Analysis for Face Recognition with Single Sample per Person," in Proc. of Asian Conference on Computer Vision, workshop FSLCV, pp. 85-95, November 1-5, 2014. Article (CrossRef Link)
14 J. Yang, D. Zhang, J.Y. Yang, “Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 1, pp. 131-137, 2004. Article (CrossRef Link)   DOI
15 R. Kumar, A. Banerjee, B.C. Vemuri, H. Pfister, "Maximizing all margins: Pushing face recognition with kernel plurality," IEEE International Conference on Computer Vision, pp. 2375-2382, November 6-13, 2011. Article (CrossRef Link)
16 S. Yu, S. Shan, X. Chen, W. Gao, "Adaptive Generic Learning for Face Recognition from a Single Sample per Person," IEEE Computer Vision and Pattern Recognition, pp. 2699-2706, June 13-18, 2010. Article (CrossRef Link)
17 J. Lu, Y.P. Tan, G. Wang, X. Zhou, "Discriminative Multi-Manifold Analysis for Face Recognition from a Single Training Sample per Person," in Proc. of IEEE International Conference on Computer Vision, PP. 1943-1950, November 6-13, 2011. Article (CrossRef Link)
18 P. F. Zhu, L. Zhang, Q.H. Hu, and S. C.K. Shiu, "Multi-scale Patch based Collaborative Representation for Face Recognition with Margin Distribution Optimization," European Conference on Computer Vision, pp. 822-835, October 7-13, 2012. Article (CrossRef Link)
19 N. C. de Condorcet, Essai sur l’Application de l’Analyze `a la Probabilit´e des D´ecisions Rendues `a la Pluralit´e des Voix. Paris, France:Imprim´erie Royale, 1785.
20 K. Lee, J. Ho, and D. Kriegman, “Acquiring Linear Subspaces for Face Recogntinon under Variable Lighting,” IEEE Transactions Pattern Analysis and Machine Intelligence, vol. 27, no. 5, pp. 684-698, 2005. Article (CrossRef Link)   DOI
21 L. Lam, C. Y. Suen, “Application of majority voting to pattern recognition: an analysis of its behavior and performance,” IEEE Transactions Systems Man and Cybernetics, Part A: Systems and Humans, vol. 27, no. 5, pp. 553-568, 1997. Article (CrossRef Link)   DOI
22 P. Belhumeur, J. Hespanha, and D. Kriegman, “Eigenfaces vs. fisherfaces: Recognition using class specific linear projection,” IEEE Transactions Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 711-720, 1997. Article (CrossRef Link)   DOI
23 A. Georghiades, P. Belhumeur, D. Kriegman, “From few to many: Illumination cone models for face recognition under variable lighting and pose,” IEEE Transactions Pattern Analysis and Machine Intelligence, vol. 6, no. 23, pp. 643-660, 2001. Article (CrossRef Link)   DOI
24 A. M. Martinez, R. Benavente, "The AR Face Database," CVC Technical Report 24, 1998.
25 Q. F. Stout, “Supporting Divide-and-Conquer Algorithms for Image Processing,” Journal of Parallel and Distributed Computing, vol. 4, no. 1, pp. 95-115, 1987. Article (CrossRef Link)   DOI
26 A. M. Martínez and A. C. Kak, “PCA versus LDA,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 2, pp. 228-233, 2001. Article (CrossRef Link)   DOI
27 X. Tan, S.C. Chen, Z.H. Zhou, and h. F., “Face recognition from a single image per person: A survey,” Pattern Recognition, vol. 39, no. 9, pp. 1725-1745, 2006. Article (CrossRef Link)   DOI
28 S. Shan, W. Gao, and D. Zhao, “Face Identification Based on Face-Specific Subspace,” International Journal of Imaging Systems and Technology, vol. 13, no. 1, pp. 23-32, 2003. Article (CrossRef Link)   DOI
29 Quan-xue Gao, Lei Zhang, and David Zhang, “Face recognition using FLDA with single training image per person,” Applied Mathematics and Computation, vol. 205, no. 2, pp. 726-734, 2008. Article (CrossRef Link)   DOI
30 A.M. Martinez, “Recognizing imprecisely localized, partially occluded, and expression variant faces from a single sample per class,” IEEE Transactions Pattern Analysis and Machine Intelligence, vol. 25, no. 6, pp. 748-763, 2002. Article (CrossRef Link)   DOI
31 S. C. Chen, J. Liu, Z. H. Zhou, “Making FLDA Applicable to Face Recognition with One Sample per Person,” Pattern Recognition, vol. 37, no. 7, pp. 1553-1555, 2004. Article (CrossRef Link)   DOI
32 M. Turk, A. Pentland, “Eigenfaces for recognition,” Journal of Cognitive Neuroscience, vol. 3, no. 1, pp. 71–86, 1991. Article (CrossRef Link)   DOI
33 W. Zhao, R. Chellappa, A. Rosenfeld, and P. J. Phillips, “Face recognition: A literature survey,” ACM Computing Surveys, vol. 35, no. 4, pp. 399–458, 2003. Article (CrossRef Link)   DOI
34 M. Kirby, L. Sirovich, “Application of the Karhunen-Loeve procedure for the characterization of human faces,” IEEE Transactions Pattern Analysis and Machine Intelligence, vol. 12, no. 1, pp. 103–108, 1990. Article (CrossRef Link)   DOI