Abstract
A novel Support Vector Machine (SVM) face recognition method using optimized Gabor features is presented in this paper. 200 Gabor features are first selected by a boosting algorithm, which are then combined with SVM to build a two-class based face recognition system. While computation and memory cost of the Gabor feature extraction process has been significantly reduced, our method has achieved the same accuracy as a Gabor feature and Linear Discriminant Analysis (LDA) based multi-class system.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Phillips, P.J., Moon, H., Rizvi, S.A., Rauss, P.J.: The FERET evaluation methodology for face-recognition algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 1090–1104 (2000)
Lades, M., Vorbruggen, J.C., Buhmann, J., Lange, J., Von der Malsburg, C., Wurtz, R.P., Konen, W.: Distortion invariant object recognition in the Dynamic Link Architecture. IEEE Transactions on Computers 42, 300–311 (1993)
Wiskott, L., Fellous, J.M., Kruger, N., von der Malsburg, C.: Face recognition by elastic bunch graph matching. IEEE Transactions on Pattern Analysis and Machine Intelligence 19, 775–779 (1997)
Mu, X.Y., Hassoun, M.H.: Combining Gabor features: summing vs.voting in human face recognition. In: 2003 IEEE International Conference on Systems, Man and Cybernetics, p. 737. IEEE Computer Society Press, Los Alamitos (2003)
Duc, B., Fischer, S., Bigun, J.: Face authentication with Gabor information on deformable graphs. IEEE Transactions on Image Processing 8, 504–516 (1999)
Jiao, F., Gao, W., Chen, X., Cui, G., Shan, S.: A face recognition method based on local feature analysis. In: Proc. of the 5th Asian Conference on Computer Vision, pp. 188–192 (2002)
Liao, R., Li, S.: Face recognition based on multiple facial features. In: Proc. of the 4th IEEE Int. Conf. on Automatic Face and Gesture Recognition, pp. 239–244. IEEE Computer Society Press, Los Alamitos (2000)
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, Corfu, Greece, 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, 467–476 (2002)
Shen, L., Bai, L., Fairhurst, M.: Gabor wavelets and General Discriminant Analysis for face identification and verification. Image and Vision Computing 25, 553–563 (2007)
Shen, L., Bai, L.: A review on Gabor wavelets for face recognition. Pattern Analysis and Applications 9, 273–292 (2006)
Zhang, W., Shan, S., Gao, W., Chang, Y.Z., Cao, B., Yang, P.: Information fusion in face identification. In: Proceedings of the 17th International Conference on Pattern Recognition, vol. 3, pp. 950–953 (2004)
Qin, J., He, Z.-S.: A SVM face recognition method based on Gabor-featured key points. In: Proceedings of the 4th International Conference on Machine Learning and Cybernetics, vol. 8, pp. 5144–5149 (2005)
Shen, L., Bai, L.: MutualBoost learning for selecting Gabor features for face recognition. Pattern Recognition Letters 27, 1758–1767 (2006)
Cristianini, N., Shawe-Taylor, J.: An introduction to Support Vector Machines and Other Kernel-based Learning Methods. Cambridge University Press, Cambridge (2000)
Freund, Y., Schapire, R.: A short introduction to boosting. Journal of Japanese Society for Artifical Intelligence 14, 771–780 (1999)
Lienhart, R., Maydt, J.: An extended set of Haar-like features for rapid object detection. In: Proc. IEEE Conference on Image Processing, pp. 900–903. IEEE Computer Society Press, Los Alamitos (2002)
Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proc. of IEEE Conf. on Computer Vision and Pattern Recognition, Kauai, Hawaii, pp. 511–518. IEEE Computer Society Press, Los Alamitos (2001)
Burges, C.J.C.: A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery 2, 121–167 (1998)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Shen, L., Bai, L., Ji, Z. (2007). A SVM Face Recognition Method Based on Optimized Gabor Features. In: Qiu, G., Leung, C., Xue, X., Laurini, R. (eds) Advances in Visual Information Systems. VISUAL 2007. Lecture Notes in Computer Science, vol 4781. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76414-4_17
Download citation
DOI: https://doi.org/10.1007/978-3-540-76414-4_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76413-7
Online ISBN: 978-3-540-76414-4
eBook Packages: Computer ScienceComputer Science (R0)