Capitalize on dimensionality increasing techniques for improving Face Recognition Grand Challenge performance

IEEE Transactions on Pattern Analysis and Machine Intelligence
Chengjun Liu

Abstract

This paper presents a novel pattern recognition framework by capitalizing on dimensionality increasing techniques. In particular, the framework integrates Gabor image representation, a novel multiclass Kernel Fisher Analysis (KFA) method, and fractional power polynomial models for improving pattern recognition performance. Gabor image representation, which increases dimensionality by incorporating Gabor filters with different scales and orientations, is characterized by spatial frequency, spatial locality, and orientational selectivity for coping with image variabilities such as illumination variations. The KFA method first performs nonlinear mapping from the input space to a high-dimensional feature space, and then implements the multiclass Fisher discriminant analysis in the feature space. The significance of the nonlinear mapping is that it increases the discriminating power of the KFA method, which is linear in the feature space but nonlinear in the input space. The novelty of the KFA method comes from the fact that 1) it extends the two-class kernel Fisher methods by addressing multiclass pattern classification problems and 2) it improves upon the traditional Generalized Discriminant Analysis (GDA) method by deriving a uni...Continue Reading

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Citations

Jan 27, 2009·Neural Networks : the Official Journal of the International Neural Network Society·Zenglin XuMichael R Lyu
Dec 17, 2014·IEEE Transactions on Pattern Analysis and Machine Intelligence·Shu LiaoAlbert C S Chung
Sep 13, 2008·IEEE Transactions on Pattern Analysis and Machine Intelligence·Yoshihisa Shinagawa
Apr 14, 2007·IEEE Transactions on Pattern Analysis and Machine Intelligence·Chengjun Liu
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Jan 20, 2009·IEEE Transactions on Neural Networks·Chengjun Liu, Jian Yang
Dec 5, 2008·IEEE Transactions on Neural Networks·Jian Yang, Chengjun Liu
Sep 12, 2008·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Zhiming Liu, Chengjun Liu
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Sep 15, 2015·Applied Optics·Yong Luo, Ye-Peng Guan

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