Abstract
This paper presents a horizontal and vertical 2D principal component analysis (2DPCA) based discriminant analysis (HVDA) method for face verification. The HVDA method, which derives features by applying 2DPCA horizontally and vertically on the image matrices (2D arrays), achieves high computational efficiency compared with the traditional PCA and/or LDA based methods that operate on high dimensional image vectors (1D arrays). The HVDA method further performs discriminant analysis to enhance the discriminating power of the horizontal and vertical 2DPCA features. Finally, the HVDA method takes advantage of the color information across two color spaces, namely, the YIQ and the YC b C r color spaces, to further improve its performance. Experiments using the Face Recognition Grand Challenge (FRGC) version 2 database, which contains 12,776 training images, 16,028 controlled target images, and 8,014 uncontrolled query images, show the effectiveness of the proposed method. In particular, the HVDA method achieves 78.24% face verification rate at 0.1% false accept rate on the most challenging FRGC experiment, i.e., the FRGC Experiment 4 (based on the ROC III curve).
Keywords
- Principal Component Analysis (PCA)
- Biometric Experimentation Environment (BEE)
- Face Recognition Grand Challenge (FRGC)
- Fisher Linear Discriminant Analysis (FLD or LDA)
- feature extraction
- face verification
- biometrics
- color space
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References
Sirovich, L., Kirby, M.: Low-dimensional procedure for characterization of human faces. J. Optical Soc. Of Am. 4, 519–524 (1987)
Turk, M., Pentland, A.: Eigenfaces for recognition. J. Cognitive Neuroscience 3(1), 71–86 (1991)
Belhumeur, P.N., Hespanha, J.P., Kriengman, D.J.: Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. IEEE Trans. Pattern Anal. Machine Intell. 19(7), 711–720 (1997)
Yang, J., Zhang, D., Frangi, A.F., Yang, J.-Y.: Two-Dimensional PCA: a New Approach to Face Representation and Recognition. IEEE Transaction on Pattern Analysis and Machine Intelligence 26(1), 131–137 (2004)
Liu, C., Wechsler, H.: Robust coding schemes for indexing and retrieval from large face databases. IEEE Trans. Image Processing 9(1), 132–137 (2000)
Liu, C.: Capitalize on Dimensionality Increasing Techniques for Improving Face Recognition Grand Challenge Performance. IEEE Trans. Pattern Analysis and Machine Intelligence 28(5), 725–737 (2006)
Shih, P., Liu, C.: Improving the Face Recognition Grand Challenge Baseline Performance Using Color Configurations Across Color Spaces. In: ICIP 2006. IEEE International Conference on Image Processing, Atlanta, GA, October 8-11 (2006)
Jain, A., Nandakumar, K., Ross, A.: Score normalization in multimodel biometric systems. Pattern Recognition 38, 2270–2285 (2005)
Hwang, W., Park, G., Lee, J.: Multiple face model of hybrid Fourier feature for large face image set. In: Proc. IEEE Conf. Computer Vision and Pattern Recognition, IEEE Computer Society Press, Los Alamitos (2006)
Phillips, P.J., Flynn, P.J., Scruggs, T., Bowyer, K.W., Chang, J., Hoffman, K., Marques, J., Min, J., Worek, W.: Overview of the Face Recognition Grand Challenge. In: Proc. IEEE Conf. Computer Vision and Pattern Recognition, IEEE Computer Society Press, Los Alamitos (2005)
Phillips, P.J., Flynn, P.J., Scruggs, T., Bowyer, W.W.: Preliminary Face Recognition Grand Challenge Results. In: FGR 2006. Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition (2006)
Phillips, P.J.: FRGC Third Workshop Presentation. In: FRGC Workshop (February 2005)
Fukunaga, K.: Introduction to Statistical Pattern Recognition, 2nd edn. Academic Press, London (1990)
Buchsbaum, W.H.: Color TV Servicing, 3rd edn. Prentice Hall, Englewood Cliffs, NJ (1975)
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Yang, J., Liu, C. (2007). Horizontal and Vertical 2DPCA Based Discriminant Analysis for Face Verification Using the FRGC Version 2 Database. In: Lee, SW., Li, S.Z. (eds) Advances in Biometrics. ICB 2007. Lecture Notes in Computer Science, vol 4642. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74549-5_88
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DOI: https://doi.org/10.1007/978-3-540-74549-5_88
Publisher Name: Springer, Berlin, Heidelberg
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