Gabor feature-based face recognition using supervised locality preserving projection

Signal Processing

Volumn 87, Issue 10, 2007, Pages 2473-2483

  Zheng, Zhonglong ^a   Yang, Fan ^a   Tan, Wenan ^a   Jia, Jiong ^a   Yang, Jie ^b  

^a ZHEJIANG NORMAL UNIVERSITY   (China)

^b SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Face recognition; Gabor wavelets; Locality preserving projection; Manifold learning; Supervised learning

Indexed keywords

DATABASE SYSTEMS; DISCRIMINANT ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; SUPERVISED LEARNING;

GABOR WAVELETS; LOCALITY PRESERVING PROJECTION; MANIFOLD LEARNING;

FACE RECOGNITION;

EID: 34249907869     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2007.03.006     Document Type: Article

References (32)

1. Jolliffe I.T. Principal Component Analysis (1986), Springer, New York
2. Klock H., and Buhmann J. Data visualization by multidimensional scaling: a deterministic annealing approach. Pattern Recognition 33 4 (1999) 651-669
3. M. Belkin, P. Niyogi, Laplacian eigenmaps and spectral techniques for embedding and clustering, Proceedings of the Conference on Advances in Neural Information Processing System, vol. 15, 2001.
4. Lee D.D., and Seung H.S. Learning the parts of objects by non-negative matrix factorization. Nature 401 (1999) 788-791
5. Barlett M.S., Ladesand H.M., and Sejnowsky T.J. Independent component representations for face recognition. Proc. SPIE 3299 (1998) 528-539
6. Roweis S.T., and Saul L.K. Nonlinear dimensionality reduction by locally linear embedding. Science 290 5500 (2000) 2323-2326
7. Tenenbaum J.B., et al. A global geometric framework for nonlinear dimensionality reduction. Science 290 5500 (2000) 2319-2323
8. Zhao W., Chellappa R., and Nandhakumar N. Empirical performance analysis of linear discriminant classifers. Proceedings of Computer Vision and Pattern Recognition (1998) 164-169
9. Z. Zheng, J. Yang. Extended LLE with Gabor Wavelet for face recognition, in: The 17th Australian Joint Conference on Artificial Intelligence, Cairns Australia, 6-10th December 2004.
10. X. He, P. Niyogi, Locality preserving projections, in: Proceedings of the Conference on Advances in Nerual Information Processing Systems, 2003.
11. He X., Yan S., et al. Face recognition using laplacianfaces. IEEE Trans. PAMI 27 3 (2005) 328-340
12. X. Zheng, D. Cai, X. He, W.-Y. Ma, X. Lin, Locality preserving clustering for image database, in: ACM Conference on Multimedia 2004, New York City, October 10-16, 2004.
13. He X., Yan S., Hu Y., and Zhang H.-J. Learning a locality preserving subspace for visual recognition. IEEE International Conference on Computer Vision (ICCV 2003) (2003), Nice, France
14. D. de Ridder, R.P.W. Duin, Locally linear embedding for classification. Technical Report PH-2002-01, Pattern Recogntion Group, Department of Imaging Science & Technology, Delft University of Technology, Delft, Netherlands, 2002.
15. Min W., Lu K., and He X. Locality preserving projection. Pattern Recognition J. 37 4 (2004) 781-788
16. Belhumeur P.N., Hespanha J.P., and Kriegman D.J. Eigenfaces vs. Fisherfaces: recognition using class specific linear projection. IEEE Trans. PAMI 19 7 (1997) 711-721
17. Swets D.L., and Weng J. Using discriminant eigenfeatures for image retrieval. IEEE Trans. PAMI 18 8 (1996) 831-836
18. Cevikalp H., Neamtu M., et al. Discriminant common vectors for face recognition. IEEE Trans. PAMI 27 1 (2005) 4-13
19. Kim T.K., and Kittler J. Locally linear discriminant analysis for multimodally distributed classes for face recognition with a single model image. IEEE Trans. PAMI 27 3 (2005) 318-327
20. Yang J., Frangi A.F., Yang J.-y., et al. KPCA plus LDA: a complete Kernel Fisher discriminant framework for feature extraction and recognition. IEEE Trans. PAMI 27 2 (2005)
21. Daugman J.G. Two-dimensional spectral analysis of cortical receptive field profiles. Vis. Res. 20 (1980) 847-856
22. Donato G., Bartlett M.S., Hager J.C., et al. Classifying facial actions. IEEE Trans. Pattern Anal. Mach. Intell. 21 (1999) 974-989
23. C. Liu, H. Wechsler, A Gabor feature classifier for face recognition, in Proceedings of the 8th IEEE International Conference on Computer Vision, Vancouver, BC, Canada, 9-12, July, 2001.
24. Turk M., and Pentland A. Eigenfaces for recognition. J. Cognitive neurosci. 3 (1991) 71-86
25. Hsu R.-L., Mohamed A.-M., and Jain A.K. Face detection in color images. IEEE Trans. PAMI 24 (2002) 696-706
26. P. Viola, M. Jones, Rapid object detection using a boosted cascade of simple features, in: Proceedings of the Conference on Computer Vision and Pattern Recognition, Kauai, HI, USA, vol 1, (2001), pp. 511-518.
27. T. Sim, S. Baker, M. Bsat, The CMU Pose, illumination, and expression (PIE) database, in: Proceedings of the IEEE International Conference of Automatic Face and Gesture Recognition, 2002.
28. Li R.-P., Mukaidono M., and Turksen I.B. A fuzzy neural network for pattern classification and feature selection. Fuzzy Sets Syst. 130 (2002) 101-108
29. I. Cohen, N. Sebe, F.G. Cozman, M.C. Cirelo, T.S. Huang, Learning Bayesian network classifiers for facial expression recognition with both labeled and unlabeled data, in: IEEE Conference on Computer Vision and Pattern Recognition, 2003.
30. Graf A.B.A., Smola A.J., and Borer S. Classification in a normalized feature space using support vector machines. IEEE Trans. PAMI 14 3 (2003) 597-605
31. Cohen I., Cozman F.G., Sebe N., Cirelo M.C., and Huang T.S. Semi-supervised learning of classifiers: theory, algorithms, and their application to human-computer interaction. IEEE Trans. PAMI 26 12 (2004) 1553-1567
32. A.M. Martinez, R. Benavente, The AR face database, CVC Technical Report # 24, 1998.