Abstract
In this paper we present a fusion technique for Support Vector Machine (SVM) scores, obtained after a dimension reduction with Bilateral-projection-based Two-Dimensional Principal Component Analysis (B2DPCA) for Gabor features. We apply this new algorithm to face verification. Several experiments have been performed with the public domain FRAV2D face database (109 subjects). A total of 40 wavelets (5 frequencies and 8 orientations) have been used. Each set of wavelet-convolved images is considered in parallel for the B2DPCA and the SVM classification. A final fusion is performed combining the SVM scores for the 40 wavelets with a raw average. The proposed algorithm outperforms the standard dimension reduction techniques, such as Principal Component Analysis (PCA) and B2DPCA.
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References
Turk, M., Pentland, A.: Eigenfaces for Recognition. Journal of Cognitive Neuroscience 3(1), 71–86 (1991)
Yang, J., et al.: Two-Dimensional PCA: A new approach to appearance-based face representation and recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 26(1), 131–137 (2004)
Kong, H., et al.: Generalized 2D principal component analysis for face image representation and recognition. Neural Networks 18(5-6), 585–594 (2005)
Daugman, J.G.: Uncertainty relation for resolution in space, spatial-frequency and orientation optimized by two-dimensional visual cortical filters. Journal of the Optical Society of America A: Optics Image Science and Vision 2(7), 1160–1169 (1985)
Chung, K.-C., Kee, S.C., Kim, S.R.: Face Recognition using Principal Component Analysis of Gabor Filter Responses. In: International Workshop on Recognition, Analysis and Tracking of Faces and Gestures in Real-Time Systems, pp. 53–57 (1999)
Liu, C.J., Wechsler, H.: Gabor feature based classification using the enhanced Fisher linear discriminant model for face recognition. IEEE Transactions on Image Processing 11(4), 467–476 (2002)
Shen, L., Bai, L.: Face recognition based on Gabor features using kernel methods. In: 6th IEEE Conference on Face and Gesture Recognition, pp. 170–175 (2004)
Fan, W., et al.: Combining Null Space-Based Gabor Features for Face Recognition. In: 17th International Conference on Pattern Recognition ICPR’04, vol. 1, pp. 330–333 (2004)
Qin, J., He, Z.-S.: A SVM face recognition method based on Gabor-featured key points. In: 4th International Conference on Machine Learning and Cybernetics, vol. 8, pp. 5144–5149 (2005)
Vapnik, V.N.: The Nature of Statistical Learning Theory. Springer, Heidelberg (1995)
Serrano, Á., et al.: Parallel Gabor PCA with fusion of SVM scores for face verification. In: 2nd International Conference on Computer Vision Theory and Applications, accepted for publication (2007)
FRAV Database, http://frav.escet.urjc.es/databases/FRAV2D/
Wiskott, L., et al.: Face recognition by Elastic Bunch Graph Matching. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(7), 775–779 (1997)
Martín de Diego, I., Muñoz, A., Moguerza, J.M.: On the Combination of Kernels for Support Vector Classifiers. Submitted
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Serrano, Á., Martín de Diego, I., Conde, C., Cabello, E., Bai, L., Shen, L. (2007). Fusion of Support Vector Classifiers for Parallel Gabor Methods Applied to Face Verification. In: Haindl, M., Kittler, J., Roli, F. (eds) Multiple Classifier Systems. MCS 2007. Lecture Notes in Computer Science, vol 4472. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72523-7_15
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DOI: https://doi.org/10.1007/978-3-540-72523-7_15
Publisher Name: Springer, Berlin, Heidelberg
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