Metric learning: A general dimension reduction framework for classification and visualization

Proceedings - International Conference on Pattern Recognition

Volumn , Issue , 2008, Pages

  Lu, Chunyuan ^a   Feng, Guocan ^a   Jiang, Jianmin ^b   Wang, Patrick ^c  

^a SUN YAT SEN UNIVERSITY   (China)

^b UNIVERSITY OF BRADFORD   (United Kingdom)

^c NORTHEASTERN UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA VISUALIZATION; PATTERN RECOGNITION; VISUALIZATION;

DATA DIMENSIONS; DIMENSION REDUCTION; DIMENSION REDUCTION ALGORITHM; EXPERIMENTAL EVIDENCE; METRIC LEARNING; NEW DIMENSIONS; SUB MANIFOLDS; SUPERVISED DIMENSION REDUCTIONS;

CLASSIFICATION (OF INFORMATION);

EID: 77957945102     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/icpr.2008.4761130     Document Type: Conference Paper

References (15)

1. M. Turk and A. Pentland. Eigenfaces for recognition. Journal of Cognitive Neuroscience, 3(1):71-86, 1991.
2. T. Cox and M. Cox. Multidimensional Scaling. Chapman & Hall, London, 1994.
3. P.N. Belhumeur, J.P. Hepanha, and D.J. Kriegman. Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Transactions on PAMI, 19(7):711-720, 1997.
4. J. B. Tenenbaum, Vin de Silva, and Johh C. Langford. A Global Geometric Framework for Nonlinear Dimensionality Reduction. Science, 290(5500):2319-2323, 2000.
5. Sam T. Roweis and Lawrence K. Saul. Nonlinear Dimensionality Reduction by Locally Linear Embedding. Science, 290(22): 2323-2326, 2000.
6. M. Belkin and P. Niyogi. Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering. Advances in NIPS 15, 2002.
7. X. He and Partha Niyogi. Locality Preserving Projections. Advances in NIPS 16, 2003.
8. X. He, D. Cai, S. Yan, H.-J. Zhang. Neighborhood preserving embedding. In Proceedings of the Tenth IEEE ICCV, 1208-1213, 2005.
9. S. Yan, D. Xu, B. Zhang, H.-J. Zhang, Q. Yang and S. Lin. Graph embedding and extension: A general framework for dimensionality reduction. IEEE Transactions on PAMI, 29(1):40-51, 2007.
10. D. Cai, X. He, Y. Hu, J. Han, and T. Huang, "Learning a Spatially Smooth Subspace for Face Recognition", IEEE Conference on CVPR, 1-7, 2007.
11. Yale University, database available from: < http://cvc.yale.edu/ projects/yalefaces/yalefaces.html>.
12. Yale University, database available from: < http://cvc.yale.edu/ projects/yalefacesB/yalefacesB.html>.
13. D. Cai, X. He and J. Han. Using Graph Model for Face Analysis. Technical Report, UIUC, 2005.
14. Y. Koren and L. Carmel, Visualization of Labeled Data Using Linear Transformations, Proceedings of IEEE Information Visualization, 121-128, 2003.
15. Xinge You, Dan Zhang, Qiuhui Chen, Patrick Wang and Yuan Yan Tang. Face Representation By Using Non-tensor Product Wavelets. ICPR, 503-506, 2006.