Discriminative K-SVD for dictionary learning in face recognition

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2010, Pages 2691-2698

  Zhang, Qiang ^a   Li, Baoxin ^a  

^a Arizona State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALTERNATIVE APPROACH; CLASSIFICATION ERRORS; DICTIONARY LEARNING; FACE DATABASE; FACE RECOGNITION SCHEMES; FISHER CRITERION; HUMAN SUBJECTS; ITERATIVE APPROXIMATIONS; LINEAR CLASSIFIERS; OBJECTIVE FUNCTIONS; OPTIMAL DISCRIMINATIONS; OPTIMIZATION PROCEDURES; OVER-COMPLETE; SUB-PROBLEMS;

ALGORITHMS; CLASSIFIERS; COMPUTATIONAL METHODS; COMPUTER VISION; DATABASE SYSTEMS; OPTIMIZATION; SINGULAR VALUE DECOMPOSITION;

FACE RECOGNITION;

EID: 77955998411     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2010.5539989     Document Type: Conference Paper

References (23)

1. M. Aharon, M. Elad, and A. Bruckstein. K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation. IEEE Transactions on signal processing, 54(11):4311, 2006. 1, 2
2. R. Basri and D. Jacobs. Lambertian reflectance and linear subspaces. IEEE Transactions on Pattern Analysis and Machine Intelligence, pages 218-233, 2003. 2
3. P. Belhumeur, J. Hespanha, and D. Kriegman. Eigenfaces vs. Fisherfaces: recognition using class specific linearprojection. IEEE Transactions on pattern analysis and machine intelligence, 19(7):711-720, 1997. 1, 2
4. O. Bryt and M. Elad. Compression of facial images using the K-SVD algorithm. Journal of Visual Communication and Image Representation, 19(4):270-282, 2008. 1
5. O. Bryt and M. Elad. Improving the k-svd facial image compression using a linear deblocking method. In IEEE 25th Convention of Electrical and Electronics Engineers in Israel, 2008. IEEEI 2008, pages 533-537, 2008. 1
6. E. Candes and J. Romberg. 11-magic: Recovery of sparse signals via convex programming. URL: www. acm. caltech. edu/l1magic/downloads/l1magic. pdf. 4
7. E. Candes, J. Romberg, and T. Tao. Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information. IEEE Transactions on information theory, 52(2):489-509, 2006. 2
8. S. Chen, C. Cowan, P. Grant, et al. Orthogonal least squares learning algorithm for radial basis function networks. IEEE Transactions on neural networks, 2(2):302-309, 1991. 4
9. D. Donoho. Compressed sensing. IEEE Transactions on Information Theory, 52(4):1289-1306, 2006. 2
10. M. Elad and M. Aharon. Image denoising via sparse and redundant representations over learned dictionaries. IEEE Transactions on Image Processing, 15(12):3736-3745, 2006. 1
11. M. Figueiredo, R. Nowak, and S. Wright. Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems. IEEE Journal on selected topics in Signal Processing, 1(4):586-597, 2007. 4
12. A. Georghiades, P. Belhumeur, and D. Kriegman. From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose. IEEE Trans. Pattern Anal. Mach. Intelligence, 23(6):643-660, 2001. 1
13. K. Lee, J. Ho, and D. Kriegman. Acquiring Linear Subspaces for Face Recognition under Variable Lighting . IEEE Trans. Pattern Anal. Mach. Intelligence, 27(5):684-698, 2005. 2, 6
14. J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman. Discriminative learned dictionaries for local image analysis. In IEEE Conference on Computer Vision and Pattern Recognition, 2008. CVPR 2008, pages 1-8, 2008. 1, 3
15. J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman. Supervised dictionary learning. Adv. NIPS, 21, 2009. 1, 3
16. J. Mairal, M. Elad, G. Sapiro, et al. Sparse representation for color image restoration. IEEE Transactions on Image Processing, 17(1):53, 2008. 1
17. A. Martinez and R. Benavente. The AR face database. Univ. Purdue, CVC Tech. Rep, 24, 1998. 2
18. D. Pham and S. Venkatesh. Joint learning and dictionary construction for pattern recognition. In IEEE Conference on Computer Vision and Pattern Recognition, 2008. CVPR 2008, pages 1-8, 2008. 1, 2, 3, 5, 6, 7, 8
19. Y. Sharon, J. Wright, and Y. Ma. Computation and relaxation of conditions for equivalence between l1 and l0 minimization. submitted to IEEE Transactions on Information Theory, 2007. 5
20. J. Tropp. Just relax: Convex programming methods for identifying sparse signals in noise. IEEE Transactions on Information Theory, 52(3):1030-1051, 2006. 4
21. M. Turk and A. Pentland. Eigenfaces for recognition. Journal of cognitive neuroscience, 3(1):71-86, 1991. 1
22. J. Wright, A. Yang, A. Ganesh, S. Sastry, and Y. Ma. Robust face recognition via sparse representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, pages 210-227, 2009. 1, 2, 6, 7
23. W. Zhao, R. Chellappa, P. Phillips, and A. Rosenfeld. Face recognition: A literature survey. Acm Computing Surveys (CSUR), 35(4):399-458, 2003. 1