Abstract
Recently, many approaches of face recognition have been proposed due to its broad applications. The generalized low rank approximation of matrices(GLRAM) was proposed in [1], and a necessary condition for the solution of GLRAM was presented in [2]. In addition to all these developments, the Two-Dimensional Principal Component Analysis (2DPCA) model is proposed and proved to be an efficient approach for face recognition [5]. In this paper, we proposed Double Sides 2DPCA algorithm via investigating the 2DPCA algorithm and GLRAM algorithm, experiments showed that the Double Sides 2DPCA’s performance is as good as 2DPCA’s and GLRAM’s. Furthermore, the computation cost of recognition is less than 2DPCA and the computation speed is faster than that for GLRAM. Further, we present a new constructive method for incrementally adding observation to the existing eigen-space model for Double Sides 2DPCA, called incremental doubleside 2DPCA. An explicit formula for such incremental learning is derived. In order to illustrate the effectiveness of the proposed approach, we performed some typical experiments.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Jieping, Y.: Generalized Low Rank Approximations of Matrices. In: The Proceedings of Twenty-first International Conference on Machine Learning, Banff, Alberta, Canada, pp. 887–894 (2004)
Lu, C., Liu, W., Senjian, A.: Revisit to the Problem of Generalized Low Rank Approximation of Matrices. In: International Conference on Intelligent Computing. ICIC, pp. 450–460 (2006)
Hall, P.M., Marshall, D., Martin, R.R.: Incremental Eigenanalysis for Classification. PAMA 22(9), 1042–1048 (2000)
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)
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)
Sirovichan, L., Kirby, M.: Low-Dimensional Procedure for Characterization of HumanFaces. J. Optical Soc. Am. 4, 519–524 (1987)
Kirbyand, M., Sirovich, L.: Application of the KL Procedure for the Characterization of Human Faces. IEEE Trans. Pattern Analysisand Machine Intelligence 12, 103–108 (1990)
Grudin, M.A.: OnInternal Representations in Face Recognition Systems. Pattern Recognition 33, 1161–1177 (2000)
Zhao, L., Yang, Y.: Theoretical Analysis of Illumination in PCA-Based Vision Systems. Pattern Recognition 32, 547–564 (1999)
Valentin, D., Abdi, H., O’Toole, A.J.G.W.: Cottrell: Connectionist Models of Face Processing: a Survey. Pattern Recognition 27, 1209–1230 (1994)
Hall, P., Marshall, D., Martin, R.: Merging and Splitting Eigenspace Models. PAMI 22, 1042–1048 (2000)
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)
Chandrasekaram, S., Manjunath, B.S., Wang, Y.F.: An Eigenspace Update Algrithm for Image Analysis. Graphical Models and Image Processing 59, 321–332 (1997)
Liu, X., Chen, T., Thomton, S.M.: Eigenspace Updating for Non-Stationary Process and its Application to Face recognition. Pattern Recognition, Special issue on Kernel and Subspace Methods for Computer Vision (Accepted for publication on, September 2002)
Tjahyadi, R., Liu, W., Venkatesh, S.: Automatic Parameter Selection for Eigenface. In: Proceeding of 6th International Conference on Optimization Techniques and Applications. ICOTA (2004)
Golub, G.H., Van Loan, C.F.: Matrix Computations, 3rd edn. The Johns Hopkins University Press, Baltimore (1996)
Helmke, U., Moore, J.: Optimization and Dynamic Systems. Springer, London (1994)
Lu, C., Liu, W., Senjian, A., Svetha, V.: Face Recognition via Incremental 2DPCA. In: International Joint Conference on AI. IJCAI, pp. 19–24 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lu, C., Liu, W., Liu, X., An, S. (2008). Double Sides 2DPCA for Face Recognition. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2008. Lecture Notes in Computer Science, vol 5226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87442-3_56
Download citation
DOI: https://doi.org/10.1007/978-3-540-87442-3_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87440-9
Online ISBN: 978-3-540-87442-3
eBook Packages: Computer ScienceComputer Science (R0)