Manifold adaptive kernel local fisher discriminant analysis for face recognition

Journal of Multimedia

Volumn 7, Issue 6, 2012, Pages 387-393

  Wang, Ziqiang ^a   Sun, Xia ^a  

^a HENAN UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Face recognition; Kernel function; Local fisher discriminant analysis; Manifold learning

Indexed keywords

ADAPTIVE KERNELS; FACE DATABASE; FACE IMAGES; FISHER DISCRIMINANT ANALYSIS; HIGH DIMENSIONALITY; KERNEL FUNCTION; LOCAL MANIFOLD STRUCTURE; MANIFOLD LEARNING; NEAREST NEIGHBORS; NON-LINEAR VARIATION;

ALGORITHMS; FISHER INFORMATION MATRIX;

FACE RECOGNITION;

EID: 84871199648     PISSN: 17962048     EISSN: None     Source Type: Journal    
DOI: 10.4304/jmm.7.6.387-393     Document Type: Article

References (23)

1. S. Zafeiriou, G. Tzimiropoulos, M. Petrou, and T. Stathaki, "Regularized kernel discriminant analysis with a robust kernel for face recognition and verification, " IEEE Transactions on Neural Networks and Learning Systems, vol. 23, pp. 526-534, March 2012.
2. A. K. Jain, B. Klare, and U. Park, "Face matching and retrieval in forensics applications, " IEEE Multimedia, vol. 19, pp. 20-20, January 2012.
3. X.-H. Han, Y.-W. Chen, and X. Ruan, "Multilinear supervised neighborhood embedding of a local descriptor tensor for scene/object recognition, " IEEE Transactions on Image Processing, vol. 21, pp. 1314-1326, March 2012.
4. A. Li, S. Shan, and W. Gao, "Coupled bias-variance tradeoff for cross-pose face recognition, " IEEE Transactions on Image Processing, vol. 21, pp. 305-315, January 2012.
5. H. Wang, S. Chen, Z. Hu, and W. Zheng, "Locality-preserved maximum information projection, " IEEE Transactions on Neural Networks, vol. 19, pp. 571-585, April 2008.
6. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification, 2nd edition. Hoboken, NJ: Wiley-Interscience, 2000.
7. D. Cai, X. He, J. Han, and H.-J. Zhang, "Orthogonal Laplacianfaces for face recognition, " IEEE Transactions on Image Processing, vol. 15, pp. 3608-3614, November 2006.
8. S. Yan, D. Xu, B. Zhang, H.-J. Zhang, Q. Yang, and S. Lin, "Graph embedding and extensions: a general framework for dimensionality reduction, " IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, pp. 40-51, January 2007.
9. X. He, S. Yan, Y. Hu, P. Niyogi, and H.-J. Zhang, "Face recognition using Laplacianfaces, " IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, pp. 328-340, March 2005.
10. T.-K. Kim, J. Kittler, and R. Cipolla, "On-line learning of mutually orthogonal subspaces for face recognition by image sets, " IEEE Transactions on Image Processing, vol. 19, pp. 1067-1074, April 2010.
11. C. Chen, J. Zhang, and R. Fleischer, "Distance approximating dimension reduction of Riemannian manifolds, " IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 40, pp. 208-217, February 2010.
12. T. Zhang, B. Fang, Y. Y. Tang, G. He, and J. Wen, "Topology preserving non-negative matrix factorization for face recognition, " IEEE Transactions on Image Processing, vol. 17, pp. 574-584, April 2008.
13. J. Tenenbaum, V. Silva, and J. Langford, "A global geometric framework for nonlinear dimensionality reduction, " Science, vol. 290, pp. 2319-2323, December 2000.
14. S. Roweis and L. Saul, "Nonlinear dimensionality reduction by locally linear embedding, " Science, vol. 290, pp. 2323-2326, December 2000.
15. M. Belkin and P. Niyogi, "Laplacian eigenmaps for dimensionality reduction and data representation, " Neural Computation, vol. 15, pp. 1373-1396, June 2003.
16. X. He, P. Niyogi, "Locality preserving projections, " in Advances in Neural Information Processing Systems, Cambridge, MA:MIT Press, 2003, pp. 385-392.
17. M. Sugiyama, "Dimensionality reduction of multimodal labeled data by local Fisher discriminant analysis, " Journal of Machine Learning Research, vol. 8, pp. 1027-1061, July 2007.
18. V. Sindhwani, P. Niyogi, and M. Belkin, "Beyond the point cloud: from transductive to semi-supervised learning, " in Proceedings of 2005 International Conference of Machine learning, New York:ACM Press, 2005, pp. 824-831.
19. V. N. Vapnik, The Nature of Statistical Learning Theory. New York: Springer-Verlag, 1995.
20. D. Cai and X. He, "Manifold adaptive experimental design for text categorization, " IEEE Transactions on Knowledge and Data Engineering, vol. 24, pp. 707-719, April 2012.
21. K. I. Kin, K. Jung, and H. J. Kim, "Face recognition using kernel principal component analysis, " IEEE Signal Processing Letters, vol. 9, pp. 40-42, February 2002.
22. Q. Liu, H. Lu, and S. Ma, "Improving kernel Fisher discriminant analysis for face recognition, " IEEE Transactions on Circuits and Systems for Video Technology, vol. 14, pp. 42-49, January 2004.
23. T. Sim, S. Baker, and M. Bsat, "The CMU pose, illuminlation, and expression database, " IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, pp. 1615-1618, December 2003.