Fractional-order embedding canonical correlation analysis and its applications to multi-view dimensionality reduction and recognition

Pattern Recognition

Volumn 47, Issue 3, 2014, Pages 1411-1424

  Yuan, Yun Hao ^a,b   Sun, Quan Sen ^b   Ge, Hong Wei ^a  

^a JIANGNAN UNIVERSITY   (China)

^b NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Canonical correlation analysis; Dimensionality reduction; Feature extraction; Multi view learning; Pattern recognition

Indexed keywords

CANONICAL CORRELATION ANALYSIS; CLASSIFICATION ACCURACY; CLASSIFICATION TASKS; DIMENSIONALITY REDUCTION; FEATURE EXTRACTION METHODS; HANDWRITTEN NUMERAL; MULTI-VIEW LEARNING; OBJECT RECOGNITION PROBLEM; COVARIANCE MATRICES;

EIGENVALUES AND EIGENFUNCTIONS; FEATURE EXTRACTION; OBJECT RECOGNITION; PATTERN RECOGNITION; CHARACTER RECOGNITION; CORRELATION METHODS; COVARIANCE MATRIX; EXTRACTION; MATRIX ALGEBRA;

COVARIANCE MATRIX; CLASSIFICATION (OF INFORMATION);

EID: 84888331774     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2013.09.009     Document Type: Conference Paper

References (58)

1. M. Sargin, Y. Yemez, E. Erzin, and A. Tekalp Audio-visual synchronization and fusion using canonical correlation analysis IEEE Transactions on Multimedia 9 7 2007 1396 1403
2. M. Slaney, M. Covell, Facesync: a linear operator for measuring synchronization of video facial images and audio tracks, in: Proceedings of Neural Information Processing Systems, 2000, pp. 814-820.
3. C.C. Chibelushi, F. Deravi, and J.S.D. Mason A review of speech-based bimodal recognition IEEE Transactions on Multimedia 4 1 2002 23 37
4. P. Glenisson, J. Mathys, and B.D. Moor Meta-clustering of gene expression data and literature-based information ACM SIGKDD Explorations Newsletter 5 2 2003 101 112
5. A.A. Nielsen Multiset canonical correlations analysis and multispectral, truly multitemporal remote sensing data IEEE Transactions on Image Processing 11 3 2002 293 305
6. A.K. Jain, R.P.W. Duin, and J. Mao Statistical pattern recognition: a review IEEE Transactions on Pattern Analysis and Machine Intelligence 22 1 2000 4 37
7. Bo Long, Philip S. Yu, Zhongfei (Mark) Zhang, A general model for multiple view unsupervised learning, in: Proceedings of the 2008 SIAM International Conference on Data Mining, 2008, pp. 822-833.
8. C. Hou, C. Zhang, Y. Wu, and F. Nie Multiple view semi-supervised dimensionality reduction Pattern Recognition 43 3 2010 720 730
9. Zhang Jintao, Jun Huan, Inductive multi-task learning with multiple view data, in: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012, pp. 543-551.
10. F. Camastra, and A. Vinciarelli Estimating the intrinsic dimension of data with a fractal-based method IEEE Transactions on Pattern Analysis and Machine Intelligence 24 10 2002 1404 1407
11. Jidong Zhao, Ke Lu, and Xiaofei He Locality sensitive semi-supervised feature selection Neurocomputing 71 2008 1842 1849
12. Xiaofei He, Ming Ji, Chiyuan Zhang, and Hujun Bao A variance minimization criterion to feature selection using laplacian regularization IEEE Transactions on Pattern Analysis and Machine Intelligence 33 10 2011 2013 2025
13. S. Bickel, T. Scheffer, Multi-view clustering, in: Proceedings of the 4th IEEE International Conference on Data Mining, 2004, pp. 19-26.
14. K. Chaudhuri, S.M. Kakade, K. Livescu, K. Sridharan, Multi-view clustering via canonical correlation analysis, in: Proceedings of the 26th Annual International Conference on Machine Learning, 2009, pp. 129-136.
15. S.M. Kakade, D.P. Foster, Multi-view regression via canonical correlation analysis, in: Proceedings of the 20th Annual Conference on Learning Theory, 2007, pp. 82-96.
16. I.T. Jolliffe Principal Component Analysis NewYork second ed. 2002 Springer-verlag
17. M. Truk, and A. Pentland Eigenfaces for recognition Journal of Cognitive Neuroscience 3 1 1991 71 86
18. K. Fukunaga Introduction to Statistical Pattern Recognition second ed. 1990 Academic Press Boston
19. P.N. Belhumeur, J.P. Hespanha, and D.J. Kriegman Eigenfaces vs. fisherfaces: recognition using class specific linear projection IEEE Transactions on Pattern Analysis and Machine Intelligence 19 7 1997 711 720
20. X. He, P. Niyogi, Locality preserving projections, in: Proceedings of the 16th Conference on Neural Information Processing Systems, 2003, pp. 585-591.
21. X. He, S. Yan, Y. Hu, P. Niyogi, and H.J. Zhang Face recognition using laplacianfaces IEEE Transactions on Pattern Analysis and Machine Intelligence 27 3 2005 328 340
22. S.T. Roweis, and L.K. Saul Nonlinear dimensionality reduction by locally linear embedding Science 290 5500 2000 2323 2326
23. Q.S. Sun, S.G. Zeng, Y. Liu, P.A. Heng, and D.S. Xia A new method of feature fusion and its application in image recognition Pattern Recognition 38 12 2005 2437 2448
24. D.P. Foster, S.M. Kakade, T. Zhang, Multi-view Dimensionality Reduction via Canonical Correlation Analysis, Technical Report TTI-TR-2008-4, 2008.
25. Y.H. Yuan, Q.S. Sun, Q. Zhou, and D.S. Xia A novel multiset integrated canonical correlation analysis framework and its application in feature fusion Pattern Recognition 44 5 2011 1031 1040
26. X.H. Chen, S.C. Chen, H. Xue, and X.D. Zhou A unified dimensionality reduction framework for semi-paired and semi-supervised multi-view data Pattern Recognition 45 5 2012 2005 2018
27. A. Kimura, H. Kameoka, M. Sugiyama, SemiCCA: efficient semi-supervised learning of canonical correlations, in: Proceedings of the 20th International Conference on Pattern Recognition, Istanbul, Turkey, 2010.
28. L. Sun, S.W. Ji, and J.P. Ye Canonical correlation analysis for multilabel classification: a least-squares formulation, extensions, and analysis IEEE Transactions on Pattern Analysis and Machine Intelligence 33 1 2011 194 200
29. I. Gonzalez, S. Dejean, P. Martin, and A. Baccini CCA: an r package to extend canonical correlation analysis Journal of Statistical Software 23 12 2008 1 14
30. T.K. Sun, and S.C. Chen Locality preserving CCA with applications to data visualization and pose estimation Image and Vision Computing 25 5 2007 531 543
31. Q.S. Sun, Z. Jin, P.A. Heng, D.S. Xia, A novel feature fusion method based on partial least squares regression, in: Proceedings of the Third International Conference on Advances in Pattern Recognition, 2005, pp. 268-277.
32. Q.S. Sun, Z.D. Liu, P.A. Heng, and D.S. Xia A theorem on the generalized canonical projective vectors Pattern Recognition 38 3 2005 449 452
33. T.K. Kim, J. Kittler, and R. Cippola Discriminative learning and recognition of image set classes using canonical correlations IEEE Transactions on Pattern Analysis and Machine Intelligence 29 6 2007 1005 1018
34. T. Melzer, M. Reiter, and H. Bischof Appearance models based on kernel canonical correlation analysis Pattern Recognition 36 9 2003 1961 1971
35. H. Hotelling Relations between two sets of variates Biometrika 28 34 1936 321 377
36. Lu Juwei, K.N. Plataniotis, and A.N. Venetsanopoulos Regularized discriminant analysis for the small sample size problem in face recognition Pattern Recognition Letters 24 16 2003 3079 3087
37. S.E. Leurgans, R.A. Moyeed, and B.W. Silverman Canonical correlation analysis when the data are curves Journal of the Royal Statistical Society B 55 3 1993 725 740
38. A. Lykou, and J. Whittaker Sparse CCA using lasso with positivity constraints Computational Statistics and Data Analysis 54 2 2010 3144 3157
39. D.R. Hardoon, and J. Shawe-Taylor Sparse canonical correlation analysis Machine Learning 83 3 2011 331 353
40. A. Hendrikse, L. Spreeuwers, R. Veldhuis, A bootstrap approach to eigenvalue correction, in: Proceedings of the 2009 Ninth IEEE International Conference on Data Mining, 2009, pp. 818-823.
41. O. Ledoit, and M. Wolf A well-conditioned estimator for large-dimensional covariance matrices Journal of Multivariate Analysis 88 2 2004 365 411
42. D. Hardoon, S. Szedmak, and J. Shawe-Taylor Canonical correlation analysis: an overview with application to learning methods Neural Computation 16 12 2004 2639 2664
43. M. Barker, and W. Rayens Partial least squares for discrimination Journal of Chemometrics 17 3 2003 166 173
44. Quan-sen Sun, Research on Feature Extraction and Image Recognition Based on Correlation Projection Analysis (Ph.D. dissertation), Nanjing University of Science and Technology, 2006.
45. Yi-Fei Pu, Ji-Liu Zhou, and Xiao Yuan Fractional differential mask: a fractional differential-based approach for multiscale texture enhancement IEEE Transactions on Image Processing 19 2 2010 491 511
46. W. Pan, K. Qin, and Y. Chen An adaptable-multilayer fractional Fourier transform approach for image registration IEEE Transactions on Pattern Analysis and Machine Intelligence 31 3 2009 400 413
47. J. Liu, S. Chen, and X. Tan Fractional order singular value decomposition representation for face recognition Pattern Recognition 41 1 2008 378 395
48. G.H. Golub, and C.F. Van Loan Matrix Computations Third ed. 1996 The Johns Hopkins University Press Baltimore, London
49. A. Hendrikse, R. Veldhuis, L. Spreeuwers, Eigenvalue correction results in face recognition, in: Proceedings of the 29th Symposium on Information Theory in the Benelux, 2008, pp. 27-35.
50. P. Xu, G.N. Brock, and R.S. Parrish Modified linear discriminant analysis approaches for classification of high-dimensional microarray data Computational Statistics and Data Analysis 53 5 2009 1674 1687
51. Z. Lou, K. Liu, J.Y. Yang, and C.Y. Suen Rejection criteria and pairwise discrimination of handwritten numerals based on structural features Pattern Analysis and Applications 2 3 1992 228 238
52. J. Yang, A.F. Frangi, J.Y. Yang, D. Zhang, and Z. Jin KPCA plus LDA: a complete kernel fisher discriminant framework for feature extraction and recognition IEEE Transactions on Pattern Analysis and Machine Intelligence 27 2 2005 230 244
53. Z.S. Hu, Z. Lou, J.Y. Yang, K. Liu, and J.Y. Sun Handwritten digit recognition based on multi-classifier combination Chinese Journal of Computers 22 4 1999 369 374
54. Yun-Hao Yuan, Quan-Sen Sun, Discriminative learning of multiset integrated canonical correlation analysis for feature fusion, in: Proceedings of the 15th International Conference on Information Fusion, 2012, pp. 882-887.
55. J. Yang, L. Zhang, J.Y. Yang, and D. Zhang From classifiers to discriminators: a nearest neighbor rule induced discriminant analysis Pattern Recognition 44 7 2011 1387 1402
56. A.M. Martinez, R. Benavente, The AR Face Database, CVC Technical Report #24, June 1998.
57. S.A. Nene, S.K. Nayar, H. Murase, Columbia Object Image Library (COIL-20), Technical Report CUCS-005-96, February 1996.
58. T.H. Cormen, C.E. Leiserson, R.L. Rivest, and C. Stein Introduction to algorithms second ed. 2001 MIT Press and McGraw-Hill