Self-adaptive Classifier Fusion for Expression-Insensitive Face Recognition
We address a self-adaptive face recognition scheme which is insensitive to facial expression variations. The proposed method takes advantage of self-adaptive classifier fusion based on facial geometry and RBF warping technology. Most previous face recognition schemes usually show vulnerability under changing facial expressions. The proposed scheme discriminates input face images into one of several context categories. The context categories are decided by unsupervised learning method based on the facial geometries that are derived from either scanned mosaic face images and/or coordinates of facial feature points. The proposed method provides a self-adaptive preprocessing and feature representation in accordance with the identified context category using the genetic algorithm and knowledge accumulation mechanism. The superiority of the proposed method is shown using FERET database where face images are relatively exposed to wide range of facial expression variation.
KeywordsFace Recognition Face Image Gabor Feature Fiducial Point Face Recognition System
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- 2.Nam, M.Y., Rhee, P.K.: An Efficient Face Recognition for Variant Illumination Condition. In: ISPACS 2005, vol. 1, pp. 111–115 (2004)Google Scholar
- 4.Martinez, A.M.: Recognizing Expression Variant Faces from a Single Sample Image per Class. In: Proc. IEEE Computer Vision and Pattern Recognition (CVPR), Madison (WI) (2003)Google Scholar
- 5.Sellahewa, H., Jassim, S.: Face Recognition in the presence of expression and/or illumination variation. In: Fourth IEEE Workshop on Automatic Identification Advanced Technologies, pp. 144–148 (2005)Google Scholar
- 10.Liu, C., Wechsler, H.: Gabor Feature Classifier for Face Recognition, Computer Vision. In: 8th IEEE International Conference, pp. 270–275 (2001)Google Scholar
- 11.Yau, S., Karim, F., Wang, Y., Wang, B., Gupta, S.: Reconfigurable Context-Sensitive Middleware for Pervasive Computing. IEEE Pervasive Computing, 33-40 (2002)Google Scholar
- 12.Faugman, J.: Uncertainty relation for resolution in space, spatial frequency, and orientation optimization by two-dimensional cortical filters. Journal Opt. Soc. Amer. 2(7), 675–676 (1985)Google Scholar
- 15.Shaokang, C., Brian, C.L.: Illumination and Expression Invariant Face Recognition with One Sample Image. In: Proceedings of the 17th International Conference on Pattern Recognition (ICPR 2004), vol. 1, pp. 300–303 (2004)Google Scholar