Sparse representation for face recognition based on constraint sampling and face alignment

Tsinghua Science and Technology

Volumn 18, Issue 1, 2013, Pages 62-67

  Wang, Jing ^a   Su, Guangda ^a   Xiong, Ying ^b   Chen, Jiansheng ^a   Shang, Yan ^a   Liu, Jiongxin ^c   Ren, Xiaolong ^a  

^a TSINGHUA UNIVERSITY   (China)

^b HARVARD UNIVERSITY   (United States)

^c Department of Earth and Environmental Sciences   (United States)

Author keywords

classification; face alignment; face recognition; feature extraction

Indexed keywords

COMBINED CONSTRAINTS; CONSTRAINT SAMPLING; FACE ALIGNMENT; FEATURE EXTRACTION METHODS; RECOGNITION ACCURACY; SHAPE FEATURES; SPARSE REPRESENTATION; SPARSE REPRESENTATION BASED CLASSIFICATIONS;

CLASSIFICATION (OF INFORMATION); FEATURE EXTRACTION;

FACE RECOGNITION;

EID: 84876274395     PISSN: 10070214     EISSN: None     Source Type: Journal    
DOI: 10.1109/TST.2013.6449409     Document Type: Article

References (20)

1. M. Turk and A. Pentland, Eigenfaces for recognition, Journal ofCognitive Neuroscience, vol. 3, no. 1, pp.71-86, 1991.
2. M. S. Bartlett, J. R. Movellan, and T. J. Sejnowski, Face recognition by independent component analysis, IEEE Trans. Neural Networks, vol. 13, no. 6, pp. 1450-1464, 2002.
3. B. Takacs, Comparing face images using the modified Hausdorff distance, Pattern Recognition, vol. 31, no. 12, pp. 1873-1881, 1998.
4. L. Wiskott, J. M. Fellous, N. Kruger, and C. V. D. Malsburg, Face recognition by elastic bunch graph matching, IEEE Trans. Pattern Analysis andMachine Intelligence, vol. 19, no. 7, pp. 775-779, 1997.
5. O. Deniz, M. Castrillon, and M. Hernandez, Face recognition using independent component analysis and support vector machines, Pattern Recognition Letters, vol. 24, no. 13, pp. 2153-2157, 2003.
6. P. N. Belhumeur and D. J. Kriegman, What is the set of images of an object under all possible illumination conditions, Int. Journal of Computer Vision, vol. 28, no. 3, pp. 245-260, 1998.
7. J. Wright, A. Y. Yang, A. Ganesh, S. S. Sastry, and Y. Ma, Robust face recognition via sparse representation, IEEE Trans. Pattern Analysis andMachine Intelligence, vol. 31, no. 2, pp. 210-227, 2009.
8. E. J. Candes and M. B. Wakin, An introduction to compressive sampling, IEEE Signal Progressing Magazine, vol. 25, no. 2, pp. 21-30, 2008.
9. K. C. Lee, J. Ho, and D. Kriegman, Acquiring linear subspaces for face recognition under variable lighting, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 5, pp. 684-698, 2005.
10. A. Martinez and R. Benavente, The AR face database, CVC Tech. Report, vol. 24, 1998.
11. A. Wagner, J. Wright, A. Ganesh, Z. Zhou, and Y. Ma, Towards a practical face recognition system: Robust registration and illumination by sparse representation, presented at the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Miami, FL, USA, 2009.
12. T. F. Cootes, G. J. Edwards, and C. J. Taylor, Active appearance models, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no. 6, pp. 681-685, 2001.
13. Y. Li, B. Chen, X. Zhang, and H. Shu, Face recognition algorithm by using sparse representation and Tchebichef moments, (in Chinese), Journal of Southeast University, vol. 42, no. 2, pp. 249-253, 2012.
14. F. Nahm, A. Perret, D. Amaral, and T. Albright, How do monkeys look at faces, Journal of Cognitive Neuroscience, vol.9,no.5,pp.611-623, 1997.
15. I. Biederman, Human image understanding: Recent research and theory, Computer Vision Graphics and Image Processing, vol. 32, no. 1, pp. 29-73, 1985.
16. W. E. L. Grimson and J. R. Meyer-Arendt, Object Recognition by Computer\-The Role of Geometric Constraints, MIT Press, 1990.
17. T. F. Cootes, C. J. Taylor, D. H. Cooper, and J. Graham, Active shape models-their training and application, Computer Vision andImage Understanding, vol. 61, no. 1, pp. 38-59, 1995.
18. T. F. Cootes, C. J. Taylor, and A. Lanitis, Multi-resolution search with active shape models, presented at the 12th IAPR International Conference on Pattern Recognition, Jerusalem, Israel, 1994.
19. J. Wang, G Su, J. Liu, and X. Ren, Facial feature point location algorithm combining improved ASM and AAM, (in Chinese), Journal ofOptoelectronics Laser, vol. 22, no. 8, pp. 1227-1230, 2011.
20. G Wen, The CAS-PEAL large-scale Chinese face database and baseline evaluations, IEEE Trans. System Man, vol. 38, no. 1, pp. 149-161, 2008.