Grassmannian regularized structured multi-view embedding for image classification

IEEE Transactions on Image Processing

Volumn 22, Issue 7, 2013, Pages 2646-2660

  Wang, Xinchao ^a   Bian, Wei ^b   Tao, Dacheng ^b  

^a EPFL   (Switzerland)

^b UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

Author keywords

Grassmann manifold; multi view image classification; subspace selection

Indexed keywords

CLASSIFICATION PERFORMANCE; COLOR AND TEXTURES; GRASSMANN MANIFOLD; GROUP SPARSITIES; MULTI-VIEW DATUM; MULTI-VIEW IMAGE; MULTI-VIEW IMAGE CLASSIFICATIONS; SUBSPACE SELECTION;

IMAGE PROCESSING; MATHEMATICAL MODELS;

IMAGE CLASSIFICATION;

EID: 84877895470     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2013.2255300     Document Type: Article

References (47)

1. J. Hamm and D. D. Lee, "Grassmann discriminant analysis: A unifying view on subspace-based learning," in Proc. Int. Conf. Mach. Learn., 2008, pp. 376-383.
2. R. Jenatton, J.-Y. Audibert, and F. Bach, "Structured variable selection with sparsity-inducing norms," J. Mach. Learn. Res., vol. 12, no. 10, pp. 2777-2824, Oct. 2011.
3. Y. Bengio, J. Paiement, P. Vincent, O. Delalleau, N. Le Roux, and M. Ouimet, "Out-of-sample extensions for LLE, Isomap, MDS, Eigenmaps, and spectral clustering," in Proc. Int. Conf. Artif. Intell. Stat., 2010, pp. 366-373.
4. Y. Bengio, P. Vincent, J. Paiement, O. Delalleau, M. Ouimet, and N. Le Roux, "Spectral clustering and kernel PCA are learning eigenfunctions, " Dept. d'Inf. et Recherche Operationnelle, Univ. Univ. de Montréal, Montreal, PQ, Canada, Tech. Rep. 1239, 2004.
5. M. A. Davenport, C. Hegde, M. F. Duarte, and R. G. Baraniuk, "Joint manifolds for data fusion," IEEE Trans. Image Process., vol. 19, no. 10, pp. 2580-2594, Oct. 2010.
6. R. K. Ando and T. Zhang, "Two-view feature generation model for semi-supervised learning," in Proc. Int. Conf. Mach. Learn., 2008, pp. 376-383.
7. A. Blum and T. Mitchell, "Combining labeled and unlabeled data with co-training," in Proc. Annu. Conf. Comput. Learn. Theory, 1998, pp. 92-100.
8. V. Sindhwani, P. Niyogi, and M. Belin, "A co-regularization approach to semi-supervised learning with multiple views," in Proc. 22nd ICML Workshop Learn. Multiple Views, 2005, pp. 74-79.
9. D. P. Foster, S. M. Kakade, and T. Zhang, "Multi-view dimension reduction via canonical correlation analysis," Toyota Technol. Inst., Chicago, IL, Tech. Rep. TTI-TR-2008-4.
10. C. Christoudias, R. Urtasun, and T. Darrell, "Multi-view learning in the presence of view disagreement," in Proc. 24th Conf. Uncertainty Artif. Intell., Jul. 2008, pp. 1-3.
11. S. M. Kakade and D. P. Foster, "Multi-view regression via canonical correlation analysis," in Proc. Annu. Conf. Comput. Learn. Theory, 2007, pp. 82-96.
12. M. Collins and Y. Singer, "Unsupervised models for named entity classification," in Proc. Joint SIGDAT Conf. Empirical Methods Natural Lang. Process. Very Large Corpora, 1999, pp. 100-110.
13. M. Belkin and P. Niyogi, "Laplacian eigenmaps for dimensionality reduction and data representation," Neural Comput., vol. 15, no. 6, pp. 1373-1396, Jun. 2003. (Pubitemid 37049796)
14. D. P. Williams, "Bayesian data fusion of multiview synthetic aperture sonar imagery for seabed classification," IEEE Trans. Image Process., vol. 18, no. 6, pp. 1239-1254, Jun. 2009.
15. B. Gökberk, H. Dutagaci, A. Ulas, L. Akarun, and B. Sankur, "Representation plurality and fusion for 3-D face recognition," IEEE Trans. Syst., Man Cybern., Part B, vol. 38, no. 1, pp. 155-173, Feb. 2008. (Pubitemid 351285022)
16. X. Wang, Z. Li, and D. Tao, "Subspaces indexing models on Grassmann manifold for image search," IEEE Trans. Image Process., vol. 20, no. 9, pp. 2627-2635, Sep. 2011.
17. A. Y. Ng, M. I. Jordan, and Y. Weiss, "On spectral clustering: Analysis and an algorithm," Adv. Neural Inf. Process. Syst., 2001, pp. 849-856.
18. P. Belhumeur, J. Hespanha, and D. Kriegman, "Eigenfaces versus fisherfaces: Recognition using class specific linear projection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 19, no. 7, pp. 711-720, Jul. 1997. (Pubitemid 127762263)
19. S. Yu, B. Krishnapuram, R. Rosales, H. Steck, and R. B. Rao, "Bayesian co-training," Adv. Neural Inf. Process. Syst., 2008, pp. 1665-1672.
20. L. K. Saul and S. T. Roweis, "Think globally, fit locally: Unsupervised learning of low dimensional manifolds," J. Mach. Learn. Res., vol. 4, pp. 119-155, Jan. 2003.
21. X. He and P. Niyogi, "Locality preserving projections," in Proc. Adv. Neural Inf. Process. Syst., 2003, pp. 153-160.
22. S. T. Roweis and L. K. Saul, "Nonlinear dimensionality reduction by locally linear embedding," Science, vol. 290, no. 5500, pp. 2323-2326, 2000. (Pubitemid 32041578)
23. D. Tao, X. Li, X. Wu, and S. J. Maybank, "General tensor discriminant analysis and Gabor features for gait recognition," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 10, pp. 1700-1715, Oct. 2007.
24. M. Belkin and P. Niyogi, "Laplacianeigenmaps and spectral techniques for embedding and clustering," Adv. Neural Inf. Process. Syst., 2001, pp. 585-591.
25. T. Zhang, D. Tao, X. Li, and J. Yang, "Patch alignment for dimension reduction," IEEE Trans. Knowl. Data Eng., vol. 21, no. 9, pp. 1299-1313, Sep. 2009.
26. T. Xia, D. Tao, T. Mei, and Y. Zhang, "Multiview spectral embedding," IEEE Trans. Syst., Man Cybern., Part B, Cybern., vol. 40, no. 6, pp. 1438-1446, Dec. 2010.
27. J. Ham, D. D. Lee, S. Mika, and B. Schölkopf, "A kernel view of the dimensionality reduction of manifolds," in Proc. Int. Conf. Mach. Learn., 2004, pp. 1-9
28. D. Cai, X. He, J. Han, and H. Zhang, "Orthogonal Laplacianfaces for face recognition," IEEE Trans. Image Process., vol. 15, no. 11, pp. 3608-3614, Nov. 2006. (Pubitemid 44615155)
29. D. Tao, X. Li, X. Wu, and S. J. Maybank, "Geometric mean for subspace selection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 2, pp. 260-274, Feb. 2009.
30. G. H. Golub and C. F. Van Loan, Matrix Computations, 2nd ed. Baltimore, MD, USA: The Johns Hopkins Univ. Press. 1989.
31. M. Wang, L. Yang, and X. S. Hua, "MSRA-MM: Bridging research and industrial societies for multimedia information retrieval," Microsoft Res. Asia, Beijing, China, Tech. Rep. Microsoft, 2009
32. K. Nigam and R. Ghani, "Analyzing the effectiveness and applicability of co-training," in Proc. Int. Conf. Inf. Knowl. Manage., 2000, pp. 86-93.
33. X. He, "Laplacian regularized D-optimal design for active learning and its application to image retrieval," IEEE Trans. Image Process., vol. 19, no. 1, pp. 254-263, Jan. 2010.
34. B. Geng, D. Tao, X. Xu, L. Yang, and X. Huang, "Ensemble manifold regularization," IEEE Trans. Pattern Anal. Mach. Intell., vol. 34, no. 6, pp. 1227-1233, Jun. 2012.
35. B. Long, P. S. Yu, and Z. Zhang, "A general model for multiple view unsupervised learning," in Proc. 8th SIAM Int. Conf. Data Mining, 2008, pp. 822-833.
36. T. Chua, J. Tang, R. Hong, H. Li, Z. Luo, and Y. Zheng, "NUS-WIDE: A real-world web image database from national university of Singapore," in Proc. ACM Conf. Image Video Retr., 2009, pp. 1-9.
37. I. Tosic and P. Frossard, "Dictionary learning in stereo image representation," IEEE Trans. Image Process., vol. 20, no. 4, pp. 921-934, Apr. 2011.
38. J. Hamm, "Subspace-based learning with Grassmann kernels," Ph.D. dissertation, Dept. Comput. Sci., Univ. Pennsylvania, Pennsylvania, PA, 2008.
39. S. Li, X. Lu, X. Hou, X. Peng, and Q. Cheng, "Learning multiview face subspaces and facial pose estimation using independent component analysis," IEEE Trans. Image Process., vol. 14, no. 6, pp. 705-712, Jun. 2005. (Pubitemid 40794803)
40. Y. Y.-C. Wong, "Differential geometry of Grassmann manifolds," Proc. Nat. Acad. Sci., vol. 57, no. 3, pp. 589-594, 1967.
41. U. Von Luxburg, "A tutorial on spectral clustering," Stat. Comput., vol. 17, no. 4, pp. 395-416, 2007.
42. H. K. Ekenel and B. Sankur, "Feature selection in the independent component subspace for face recognition," Pattern Recognit. Lett., vol. 25, no. 12, pp. 1377-1388, Sep. 2004.
43. L. Qiu, Y. Zhang, and C. Li, "Unitarily invariant metrics on the Grassmann space," SIAM J. Matrix Anal. Appl., vol. 27, no. 2, pp. 507-531, 2005.
44. C. Duran, L. Mata-Lorenzao, and L. Recht, "Natural variational problems in the Grassmann manifold of a C-algebra with trace," Adv. Math., vol. 154, no. 1, pp. 196-228, 2000.
45. B. Xie, Y. Mu, D. Tao, and K. Huang, "M-SNE: Multiview stochasticneighbor embedding," IEEE Trans. Syst., Man, Cybern., Part B, Cybern., vol. 41, no. 4, pp. 1088-1096, Aug. 2011.
46. J. Yu, M. Wang, and D. Tao, "Semisupervised multiview distance metric learning for cartoon synthesis," IEEE Trans. Image Process., vol. 21, no. 11, pp. 4636-4648, Nov. 2012.
47. J. Yu, D. Liu, D. Tao, and H. S. Seah, "On combining multiple features for cartoon character retrieval and clip synthesis," IEEE Trans. Syst., Man, Cybern., Part B, vol. 42, no. 5, pp. 1413-1427, Oct. 2012.