Incremental linear discriminant analysis using sufficient spanning set approximations

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

Volumn , Issue , 2007, Pages

  Kim, Tae Kyun ^a   Wong, Shu Fai ^a   Stenger, Björn ^b   Kittler, Josef ^c   Cipolla, Roberto ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^b TOSHIBA CORPORATION   (Japan)

^c UNIVERSITY OF SURREY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; COMPUTATIONAL COMPLEXITY; DATABASE SYSTEMS; IMAGE COMPRESSION; PROBLEM SOLVING; SET THEORY;

DATA DIMENSION; DATA MATRIX; SET APPROXIMATION;

DISCRIMINANT ANALYSIS;

EID: 34948839462     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2007.382985     Document Type: Conference Paper

References (15)

1. T.-J. Chin and D. Suter. Incremental Kernel PCA for Efficient Non-linear Feature Extraction. In BMVC, 2006.
2. K. Fukunaga. Introduction to statistical pattern recognition. Academic Press, Boston, 1990.
3. P. Hall, D. Marshall, and R. Martin. Merging and splitting eigenspace models. IEEE Trans. on PAMI, 22(9): 1042-1049, 2000.
4. K. Hiraoka, K. Hidai, M. Hamahira, H. Mizoguchi, T. Mishima, and S. Yoshizawa. Successive learning of linear discriminant analysis: Sanger-type algorithm. In ICPR, 2000.
5. T. Kamei, A. Yamada, T. Kim, H. Kim, W. Hwang, S. Kee. Advanced face descriptor using Fourier and inten-sity LDA features. ISO/IEC JTC1/SC29/WG11 M8998, Oct 2002.
6. T.-K. Kim, H. Kim, W. Hwang, and J. Kittler. Component-based LDA face description for image retrieval and MPEG-7 standardisation. Image and Vision Computing, 23:631-642, 2005.
7. R.-S. Lin, D. Ross, J. Lim, and M.-H. Yang. Adaptive discriminative generative model and its applications. In NIPS, 2005.
8. B. S. Manjunath, P. P. Salembier, and T. Sikora. Introduction to MPEG-7: Multimedia Content Description Interface. Wiley, New York, 2002.
9. S. Pang, S. Ozawa, and N. Kasabov. Incremental linear discriminant analysis for classification of data streams. IEEE Trans. on System, Man and Cybernetics, pages 905-914, 2005.
10. D. Skocaj and A. Leonardis. Weighted and robust incremental method for subspace learning. In ICCV, 2003.
11. Y. Wu and S. Huang. View-independent recognition of hand postures. In CVPR, pages 2088-2094, 2000.
12. X. Tao, J. Ye, Q. Li, R. Janardan, and V. Cherkassky. Efficient Kernel Discriminant Analysis via QR Decomposition. In MPS, 2004.
13. J. Yan, B. Zhang, S. Yan, Q. Yang, and H. Li. IMMC: Incremental maximum margin criterion. In Int'l Conf. Knowledge Discovery and Data Mining, 2004.
14. J. Ye, Q. Li, H. Xiong, H. Park, V. Janardan, and V. Kumar. IDR/QR: An incremental dimension reduction algorithm via QR decomposition. IEEE Trans. on Knowledge and Data Engineering, 17(9): 1208-1222, 2005.
15. X. Zhu. Semi-Supervised learning literature survey. Computer Sciences TR 1530, University of Wisconsin-Madison, 2006.