Enhancing bilinear subspace learning by element rearrangement

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 31, Issue 10, 2009, Pages 1913-1920

  Xu, Dong ^a   Yan, Shuicheng ^b   Lin, Stephen ^c   Huang, Thomas S ^d   Chang, Shih Fu ^e  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^c MICROSOFT RESEARCH ASIA   (China)

^d UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^e Columbia University ^*  (United States)

Author keywords

Bilinear subspace learning; Dimensionality reduction; Earth mover's distance; Element rearrangement

Indexed keywords

BILINEAR SUBSPACE LEARNING; CLASSIFICATION ACCURACY; DATA MATRICES; DIMENSIONALITY REDUCTION; EARTH MOVER'S DISTANCE; ELEMENT REARRANGEMENT; INFORMATION REDUNDANCIES; INTEGER PROGRAMMING PROBLEMS; ITERATIVE ALGORITHM; LOW RANK APPROXIMATIONS; MATRIX; MATRIX STRUCTURE; SUBSPACE LEARNING;

DATA COMPRESSION; EDUCATION; INTEGER PROGRAMMING; MATRIX ALGEBRA;

LEARNING ALGORITHMS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; FACE; INFORMATION PROCESSING; METHODOLOGY; NORMAL DISTRIBUTION; PHYSIOLOGY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DATA COMPRESSION; FACE; NORMAL DISTRIBUTION;

EID: 69549135109     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2009.51     Document Type: Article

References (26)

1. M. Turk and A. Pentland, "Face Recognition Using Eigenfaces," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 586-591, 1991.
2. P. Belhumeur, J. Hespanha, and D. Kriegman, "Eigenfaces versus Fisher-faces: Recognition Using Class Specific Linear Projection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 711-720, July 1997.
3. M. Vasilescu and D. Terzopoulos, "Multilinear Subspace Analysis for Image Ensembles," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 93-99, 2003.
4. H. Chen, H. Chang, and T. Liu, "Local Discriminant Embedding and Its Variants," Proc. IEEE Conf. Computer Vision and Pattern Recognition pp. 846-852, 2005.
5. G. Dai and D. Yeung, "Tensor Embedding Methods," Proc. Assoc. for the Advancement of Artificial Intelligence, pp. 330-335, 2006.
6. D. Tao, X. Li, W. Hu, S.J. Maybank, and X. Wu, "Supervised Tensor Learning," Proc. IEEE Conf. Data Mining, pp. 450-457, 2005.
7. D. Tao, X. Li, X. Wu, and S.J. Maybank, "General Tensor Discriminant Analysis and Gabor Features for Gait Recognition," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 29, no. 10, pp. 1700-1715, Oct. 2007.
8. D. Xu, S. Yan, L. Zhang, H. Zhang, Z. Liu, and H. Shum, "Concurrent Subspace Analysis," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 203-208, 2005.
9. S. Yan, D. Xu, Q. Yang, L. Zhang, X. Tang, and H. Zhang, "Discriminant Analysis with Tensor Representation," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 526-532, 2005.
10. J. Yang, D. Zhang, A. Frangi, and J. Yang, "Two-Dimensional pca: A New Approach to Appearance-Based Face Representation and Recognition," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 1, pp. 131-137, Jan. 2004.
11. J. Ye, "Generalized Low Rank Approximations of Matrices," Machine Learning, vol. 61, pp. 167-191, 2005.
12. J. Ye, R. Janardan, and Q. Li, "Two-Dimensional Linear Discriminant Analysis," Advances in Neural Information Processing Systems, pp. 1569-1576, MIT Press, 2004.
13. E. Simoncelli and B. Olshausen, "Natural Image Statistics and Neural Representation," Ann. Rev. Neuroscience, vol. 24, pp. 1193-1216, 2001.
14. G. Nemhauser and L. Wolsey, Integer and Combinatorial Optimization Wiley, 1988.
15. Y. Rubner, C. Tomasi, and L. Guibas, "The Earth Mover's Distance as a Metric for Image Retrieval," Int'l J. Computer Vision, vol. 40, no. 2, pp. 99-121, Nov. 2000.
16. P. Jensen and J. Bard, Operations Research Models and Methods. John Wiley and Sons, 2003.
17. S. Yan, D. Xu, B. Zhang, H. Zhang, Q. Yang, and S. Lin, "Graph Embedding and Extensions: A General Framework for Dimensionality Reduction," IEEE Trans. Pattern Analysis and Machine Intelligence vol. 29, no. 1, pp. 40-51, Jan. 2007.
18. T. Jebara, "Images as Bags of Pixels," Proc. IEEE Conf. Computer Vision, pp. 265-272, 2003.
19. T. Jebara, "Convex Invariance Learning," Proc. Int'l Conf. Artificial Intelligence and Statistics, 2003.
20. T. Jebara, "Kernelizing Sorting, Permutation and Alignment for Minimum Volume PCA," Proc. Conf. Learning Theory, 2004.
21. P. Shivaswamy and T. Jebara, "Permutation Invariant svms," Proc. Int'l Conf. Machine Learning, 2006.
22. T. Sim, S. Baker, and M. Bsat, "The CMU Pose, Illumination, and Expression Database," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 12, pp. 1615-1618, Dec. 2003.
23. P. Phillips, H. Moon, S. Rizvi, and P. Rauss, "The Feret Evaluation Methodology for Face-Recognition Algorithms," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 10, pp. 1090-1104, Oct. 2000.
24. S. Yan, D. Xu, S. Lin, T. Huang, and S.-F. Chang, "Element Rearrangement for Tensor-Based Subspace Learning," Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2007.
25. X. He, S. Yan, Y. Hu, P. Niyogi, and H. Zhang, "Face Recognition Using Laplacianfaces," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 3, pp. 328-340, Mar. 2005.
26. J. Munkres, "Algorithms for the Assignment and Transportation Problems," J. SIAM, vol. 5, no. 1, pp. 32-38, Mar. 1957.