Double sides 2DPCA for face recognition

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5226 LNCS, Issue , 2008, Pages 446-459

  Lu, Chong ^a,b,c   Liu, Wanquan ^b   Liu, Xiaodong ^a   An, Senjian ^b  

^a DALIAN UNIVERSITY OF TECHNOLOGY   (China)

^b CURTIN UNIVERSITY   (Australia)

^c YiLi Normal College   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BOOLEAN FUNCTIONS; LEARNING SYSTEMS; PRINCIPAL COMPONENT ANALYSIS;

2DPCA ALGORITHMS; BROAD APPLICATIONS; COMPUTATION COSTS; COMPUTATION SPEEDS; CONSTRUCTIVE METHODS; EXPLICIT FORMULAS; INCREMENTAL LEARNINGS; LOW RANK APPROXIMATIONS; PRINCIPAL COMPONENTS; SPACE MODELS;

FACE RECOGNITION;

EID: 56549116306     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-87442-3_56     Document Type: Conference Paper

References (18)

1. Ye, J.P.: Generalized Low Rank Approximations of Matrices. In: The Proceedings of Twenty-first International Conference on Machine Learning, Banff, Alberta, Canada, pp. 887-894 (2004)
2. Lu, C., Liu, W.Q., An, S.J.: Revisit to the Problem of Generalized Low Rank Approximation of Matrices. In: International Conference on Intelligent Computing. ICIC, pp. 450-460 (2006)
3. Hall, P.M., Marshall, D., Martin, R.R.: Incremental Eigenanalysis for Classification. PAMA 22(9), 1042-1048 (2000)
4. Artač, M., et al.: Incremental PCA for on-line visual learning and recognition. In: IEEE, 16th international conference on Pattern Recognition, pp. 781-784 (2002)
5. Yang, J., et al.: Two-Dimentional PCA: a new approach of 2DPCA to appearance-based face representation and recognition. IEEE Tran. Pattern Analysisand Machine Intelligence 26(11), 131-137 (2004)
6. Sirovich, L., Kirby, M.: Low-Dimensional Procedure for Characterization of HumanFaces. J. Optical Soc. Am. 4, 519-524 (1987)
7. Kirby, M., Sirovich, L.: Application of the KL Procedure for the Characterization of Human Faces. IEEE Trans. Pattern Analysisand Machine Intelligence 12, 103-108 (1990)
8. Grudin, M.A.: On Internal Representations in Face Recognition Systems. Pattern Recognition 33, 1161-1177 (2000)
9. Zhao, L., Yang, Y.: Theoretical Analysis of Illumination in PCA-Based Vision Systems. Pattern Recognition 32, 547-564 (1999)
10. Valentin, D., Abdi, H., O'Toole, A.J., Cottrell, G.W.: Connectionist Models of Face Processing: a Survey. Pattern Recognition 27, 1209-1230 (1994)
11. Hall, P., Marshall, D., Martin, R.: Merging and splitting eigenspace models. PAMI 22, 1042-1048 (2000)
12. Winkeler, J., Manjunath, B.S., Chandrasekaran, S.: Subset selection for active object recognition. In: CVPR, June 2, pp. 511-516. IEEE Computer Society Press, Los Alamitos (1999)
13. Tjahyadi, R., Liu, W.Q., Venkatesh, S.: Automatic Parameter selection for Eigenface. In: Proceeding of 6th International Conference on Optimization Techniques and Applications. ICOTA (2004)
14. ftp://plucky.cs.yale.edu/CVC/pub/images/yalefaceB/Tarsets
15. http://www.library.cornell.edu/nr/bookcpdf.html
16. Golub, G.H., Van Loan, C.F.: Matrix computations, 3rd edn. The Johns Hopkins University Press, Baltimore (1996)
17. Helmke, U., Moore, J.B.: Optimization and Dynamic Systems. Springer, London (1994)
18. Lu, C., Liu, W.Q., An, S.J., Venkatesh, S.: Face Recognition via Incremental 2DPCA. In: International Joint Conference on AI. IJCAI, pp. 19-24 (2007)