Fast haar transform based feature extraction for face representation and recognition

IEEE Transactions on Information Forensics and Security

Volumn 4, Issue 3, 2009, Pages 441-450

  Pang, Yanwei ^a   Li, Xuelong ^b   Yuan, Yuan ^c   Tao, Dacheng ^d   Pan, Jing ^e  

^a TIANJIN UNIVERSITY   (China)

^b XI AN INSTITUTE OF OPTICS AND PRECISION MECHANICS   (China)

^c ASTON UNIVERSITY   (United Kingdom)

^d NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^e TIANJIN UNIVERSITY OF TECHNOLOGY AND EDUCATION   (China)

Author keywords

Face representation and recognition; Fast algorithm; Feature extraction; Haar transform; Subspace analysis

Indexed keywords

FACE DATABASE; FACE REPRESENTATION AND RECOGNITION; FACE REPRESENTATIONS; FAST ALGORITHM; FAST HAAR TRANSFORMS; FEATURE SUBSPACE; FLOATING POINT MULTIPLICATION; HAAR TRANSFORM; HIGH DIMENSIONAL DATA; IMAGE PROJECTION; LOW-DIMENSIONAL SUBSPACE; SUBSPACE ANALYSIS; SUBSPACE LEARNING;

DISCRIMINANT ANALYSIS; FACE RECOGNITION; PRINCIPAL COMPONENT ANALYSIS;

FEATURE EXTRACTION;

EID: 69749118031     PISSN: 15566013     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIFS.2009.2026455     Document Type: Article

References (28)

1. 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., vol.19, no.7, pp. 711-720, Jul. 1997.
2. D. Cai, X. He, and J. Han, "SRDA: An efficient algorithm for large-scale discriminant analysis," IEEE Trans. Knowl. Data Eng., vol.20, no.1, pp. 1-12, Jan. 2008.
3. P. Getreur, Writing Fast Matlab Code 2008 [Online]. Available: www. eng.auburn.edu/∼dmbevly/matlab/
4. X. He, D. Cai, and J. Han, "Learning a maximum margin subspace for image retrieval," IEEE Trans. Knowl. Data Eng., vol.20, no.2, pp. 189-201, Feb. 2008.
5. X. He, S. Yan, Y. Hu, P. Niyogi, and H. Zhang, "Face recognition using Laplacian faces," IEEE Trans. Pattern Anal. Mach. Intell., vol.27, no.3, pp. 328-340, Mar. 2005.
6. Y. Fu and T. S. Huang, "Image classification using correlation tensor analysis," IEEE Trans. Image Process., vol.17, no.2, pp. 226-234, Feb. 2008.
7. Y. Fu, S. Yan, and T. Huang, "Classification and feature extraction by simplexization," IEEE Trans. Inf. Forensics Security, vol.3, no.1, pp. 91-100, Mar. 2008.
8. Y. Fu, S. Yan, and T. S. Huang, "Correlation metric for generalized feature extraction," IEEE Trans. Pattern Anal. Mach. Intell., vol.30, no.12, pp. 2229-2235, Dec. 2008.
9. T. Kim, J. Kittler, and R. Cipolla, "Discriminative learning and recognition of image set classes using canonical correlations," IEEE Trans. Pattern Anal. Mach. Intell., vol.29, no.6, pp. 1005-1018, Jun. 2007.
10. E. Oja, Subspace Methods of Pattern Recognition. Letchworth, Hertfordshire, England: Research Studies Press, 1983.
11. N. M. Oliver, B. Rosario, and A. P. Pentland, "A Bayesian computer vision system for modeling human interactions," IEEE Trans. Pattern Anal. Mach. Intell., vol.22, no.8, pp. 831-843, Aug. 2000.
12. J. Pan, Y. Pang, X. Li, Y. Yuan, and D. Tao, "A fast feature extraction method," in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, 2009, pp. 1797-1800.
13. Y. Pang, D. Tao, Y. Yuan, and X. Li, "Binary two-dimensional PCA," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol.38, no.3, pp. 1176-1780, Aug. 2008.
14. Y. Pang, Y. Yuan, and X. Li, "Generalised nearest feature line for subspace learning," Electron. Lett., vol.43, no.20, pp. 1079-1080, 2007.
15. Y. Pang and L. Zhang et al., "Neighborhood preserving projections (NPP): A novel linear dimension reduction method," Lecture Notes in Computer Science, vol.3644, pp. 117-125, 2005.
16. P. S. Penev and L. Sirovich, "The global dimensionality of face space," in Proc. IEEE Int. Conf. Automatic Face and Gesture Recognition, 2000, pp. 264-270.
17. P. J. Phillips, H. Moon, S. A. Rivzi, and P. J. Rauss, "The FERET evaluation methodology for face-recognition algorithms," IEEE Trans. Pattern Anal. Mach. Intell., vol.22, no.10, pp. 1090-1104, Oct. 2000.
18. P. R. Roeser and M. E. Jernigan, "Fast Haar transform," IEEE Trans. Comput., vol.C-31, no.2, pp. 175-177, Feb. 1982.
19. F. Tang, R. Crabb, and H. Tao, "Representing images using nonorthog-onal Haar-like bases," IEEE Trans. Pattern Anal. Mach. Intell., vol.29, no.12, pp. 2120-2134, Dec. 2007.
20. F. Tang and H. Tao, "Fast linear discriminant analysis using binary bases," Pattern Recognit. Lett., vol.28, pp. 2209-2218, 2007.
21. D. Tao, X. Tang, and X. Li, "Which components are important for interactive image searching?," IEEE Trans. Circuits Syst. Video Technol., vol.18, no.1, pp. 3-11, Jan. 2008.
22. M. Turk and A. Pentalnd, "Eigenfaces for recognition," J. Cognitive Neurosci., vol.3, no.1, pp. 71-86, 1991.
23. D. Xu, S. Yan, D. Tao, X. Li, X. Tang, and H.-J. Zhang, "Human gait recognition with matrix representation," IEEE Trans. Circuits Syst. Video Technol., vol.16, no.7, pp. 896-903, Jul. 2006. (Pubitemid 44192205)
24. D. Xu, S. Yan, D. Tao, S. Lin, and H. Zhang, "4Marginal fisher analysis and its variants for human gait recognition and content-based image retrieval," IEEE Trans. Image Process., vol.16, no.11, pp. 2811-2821, Nov. 2007.
25. S. Yan, J. Liu, X. Tang, and T. Huang, "A parameter-free framework for general supervised subspace learning," IEEE Trans. Inf. Forensics Security, vol.2, no.1, pp. 69-76, Mar. 2007.
26. ORL Face Database [Online]. Available: http://www.cl.cam.ac.uk/re-search/ dtg/attarchive/facedatabase.html 2008
27. D. Tao, X. Li, X. Wu, and S. J. Maybank, "General tensor discriminant analysis and gabor features for gait recognition," IEEE Trans. Pattern Anal. Mach. Intell., vol.29, no.10, pp. 1700-1715, Oct. 2007.
28. D. Tao, X. Li, X. Wu, and S. J. Maybank, "Geometric mean for subspace selection," IEEE Trans. Pattern Anal. Mach. Intell., vol.31, no.2, pp. 260-274, Feb. 2009.