Abstract
This paper proposes the AdaBoost Gabor Fisher Classifier (AGFC) for robust face recognition, in which a chain AdaBoost learning method based on Bootstrap re-sampling is proposed and applied to face recognition with impressive recognition performance. Gabor features have been recognized as one of the most successful face representations, but it is too high dimensional for fast extraction and accurate classification. In AGFC, AdaBoost is exploited to select optimally the most informative Gabor features (hereinafter as AdaGabor features). The selected low-dimensional AdaGabor features are then classified by Fisher discriminant analysis for final face identification. Our experiments on two large-scale face databases, FERET and CAS-PEAL (with 5789 images of 1040 subjects), have shown that the proposed method can effectively reduce the dimensionality of Gabor features and greatly increase the recognition accuracy. In addition, our experimental results show its robustness to variations in facial expression and accessories.
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References
Chellappa, R., Wilson, C.L., Sirohey, S.: Human and Machine Recognition of faces: A survey. In: Proceedings of the IEEE, vol. 83(5) (1995)
Phillips, P.J., Moon, H., et al.: The FERET Evaluation Methodology for Face-Recognition Algorithms. IEEE Trans. on Pattern Analysis and Machine Intelligence 22(10), 1090–1104 (2000)
Philips, P.J., Grother, P.J., Micheals, R.J., Blackburn, D.M., Tabassi, E., Bone, J.M.: Face Recognition Vendor Test 2002: Evaluation report, Technical Report, NISTIR 6965, National Institute of Standards and Technology (2003), http://www.frvt.org
Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification, 2nd edn. John Wiley & Sons Inc., Chichester (2001)
Lai, J., Yuen, P.C., Feng, G.C.: Face recognition using Holistic Fourier Invariant Features. Pattern Recognition 34(1), 95–109 (2001)
Lades, M., Vorbruggen, J.C., Buhmann, J., Lange, J., van der Malsburg, C., Wurtz, R.P., Konen, W.: Distortion Invariant Object Recognition in the Dynamic Link Architecture. IEEE Trans. on Computers 42(3), 300–311 (1993)
Wiskott, L., Fellous, J.M., Kruger, N., van der Malsburg, C.: Face Recogniton by Elastic Bunch Graph Matching. IEEE Trans. on PAMI 19(7), 775–779 (1997)
Krueger, V.: Gabor wavelet networks for object representation. In: DAGM Symposium, Kiel, Germany, vol. 9, pp. 13–15 (2000)
Liu, C., Wechsler, H.: Gabor Feature Based Classification Using the Enhanced Fisher Linear Discriminant Model for Face Recognition. IEEE Trans. Image Processing 11(4), 467–476 (2002)
Daugman, J.G.: Uncertainty Relation for Resolution in Space, Spatial Frequency, and Orientation Optimized by Two-Dimensional Visual Cortical Filters. J. Optical Soc. Amer. 2(7), 1,160–1,169 (1985)
Lee, T.S.: Image Representation Using 2d Gabor Wavelets. IEEE Trans. Pattern Analysis and Machine Intelligence 18(10), 959–971 (1996)
Shan, S., Gao, W., Chang, Y., Cao, B., Yang, P.: Review the Strength of Gabor features for face recognition from the angle of its robustness to mis-alignment. In: Proceedings of ICPR 2004, vol. I, pp. 338–341 (2004)
Freund, Y., Schapire, R.E.: A decision-theoretic generalization of on-line learning and an application to boosting. J. Comput. Syst. Sci. 55(1), 119–139 (1997)
Viola, P., Jones, M.: Rapid Object Detection using a Boosted Cascade of Simple. In: Proceedings of CVPR 2001, vol. I, pp. 511–518 (2001)
Li, S.Z., Zhang, Z.Q.: FloatBoost Learning and Statistical Face Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence (2004) (Accepted)
Yang, P., Shan, S., Gao, W., Li, S.Z., Zhang, D.: Face Recognition Using Ada-Boosted Gabor Features. In: Proceeding of the 6th IEEE International Conference on Automatic Face and Gesture Recognition, Korea, pp. 356–361 (May 2004)
Moghaddam, B., Jebara, T., Pentland, A.: Bayesian Face Recognition. Pattern Recognition 33, 1771–1782 (2000)
Bellhumer, P.N., Hespanha, J., Kriegman, D.: Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence, Special Issue on Face Recognition 17(7), 711–720 (1997)
Gao, W., Cao, B., Shan, S., et al.: The CAS-PEAL Larege-Scale Chinese Face Database and Evaluation Protocols, Technical Report JDL-TR-04-FR-001, Joint Research&Development Laboratory, CAS (2004), http://www.jdl.ac.cn/peal/index.html
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Shan, S., Yang, P., Chen, X., Gao, W. (2005). AdaBoost Gabor Fisher Classifier for Face Recognition. In: Zhao, W., Gong, S., Tang, X. (eds) Analysis and Modelling of Faces and Gestures. AMFG 2005. Lecture Notes in Computer Science, vol 3723. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564386_22
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DOI: https://doi.org/10.1007/11564386_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29229-6
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