Directional independent component analysis with tensor representation

26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Volumn , Issue , 2008, Pages

  Zhang, Lei ^a   Gao, Quanxue ^a,b   Zhang, David ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^b XIDIAN UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BLIND SOURCE SEPARATION; CLUSTERING ALGORITHMS; COMPUTATIONAL METHODS; COMPUTER VISION; FACE RECOGNITION; FEATURE EXTRACTION; HEMODYNAMICS; IMAGE PROCESSING; LEARNING ALGORITHMS; PATTERN RECOGNITION; TENSORS; VECTORS;

COMPUTATIONAL COSTS; CONVENTIONAL INDEPENDENT COMPONENT ANALYSIS; DIRECTIONAL IMAGES; DIRECTIONAL INFORMATIONS; FACE AND PALMPRINT; HIGH-DIMENSIONAL DATA; HIGH-DIMENSIONAL DATASET; INDEPENDENT COMPONENTS; INPUT IMAGES; K-MATRIX; MULTILINEAR ICA; RECOGNITION ACCURACY; SMALL SAMPLE SIZE; SUBSPACE ANALYSIS; TENSOR REPRESENTATION; TRAINING IMAGES;

INDEPENDENT COMPONENT ANALYSIS;

EID: 51949109825     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2008.4587667     Document Type: Conference Paper

References (19)

1. 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 Anal. Mach. Intell, 29(1):40-51, 2007.
2. M. Turk and A. Pentland. Eigenfaces for recognition. Journal of Cognitive Neuroscience, 3(1):72-86, 1991.
3. M. S. Bartlett, J. R. Movellan and T. J. Sejnowski. Face recognition by independent component analysis. IEEE Trans. on Neural Networks, 13(6):1450-1464, 2002.
4. M. Alex O. Vasilescu and D. Terzopoulos. Multilinear Independent Component Analysis. In Proc. Of IEEE Conference on Computer Vision and Pattern Recognition (CVPR05), 2005.
5. A. Hyvärinen, J. Karhunen, and E. Oja. Independent component analysis. Wiley, New York, 2001.
6. B. Moghaddam. Principal manifolds and probabilistic subspaces for visual recognition. IEEE Trans. IEEE Trans. Pattern Anal. Mach. Intell, 24(6):780-788, 2002.
7. M. A. Vicente, P. O. Hoyer, and A. Hyvärinen. Equivalence of some common linear feature extraction techniques for appearance-based object recognition tasks. IEEE Trans. Pattern Anal. Mach. Intell, 29(5):896-900, 2007.
8. M. Bressan and J. Vitrià. On the selection and classification of independent features. IEEE Trans. Pattern Anal. Mach. Intell, 25(10): 1312-1317, 2003.
9. J. Kim, J. M. Choi, J. Yi, M. Turk. Effective representation using ICA for face recognition robust to local distortion and partial occlusion. IEEE Trans. Pattern Anal. Mach. Intell. 27(12):1977-1981, 2005.
10. J. Yang, D. Zhang, A. F. Frangi, and J. Y. Yang. Two-dimensional PCA: a new approach to appearance-based face representation and recognition. IEEE Trans. Pattern Anal. Mach. Intell, 26(1): 131-137, 2004.
11. D. Tao, X. Li, X. Wu. General Tensor Discriminant Analysis and Gabor Features for Gait Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 29(10): 1700-1715, 2007.
12. S. Yan, D. X, Q, Yang, L. Zhang, X. Tang and H. Zhang. Discriminant analysis with tensor representation. In proc. Of IEEE conference on Computer Vision and Pattern Recognition (CVPR), 2005.
13. T. Kim, S. Wong, and R. Cipolla. Tensor canonical correlation analysis for action classification. In proc. Of IEEE conference on Computer Vision and Pattern Recognition (CVPR), 2007.
14. L. Lathauwer, B. Moor, and J. Vandewalle. A multilinear singular value decomposition. SIAM J. Matrix Anal. Appl., 21(4): 1253-1278, 2000.
15. UMIST Face Database, Daniel Graham, http://images.ee.umist.ac.uk/danny/ database.html, 2005.
16. The AR Face Database, http://rvl1.ecn.purdue.edu/~aleix/aleix _face_DB. html.
17. J.Ye. Generalized low rank approximations of matrices. Machine Learning, 61:167-191, 2005.
18. P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman. Eigenfaces vs. Fisherfaces: recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell, 19(7): 711-720, 1997.
19. K. Liu, Y. Cheng and J. Yang. Algebraic feature extraction for image recognition based on an optimal discriminant criterion. Pattern Recognition, 26(6): 903-911, 1993.