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2007
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Hierarchical Ensemble of Global and Local Classifiers for Face Recognition

8 years 11 months ago
Hierarchical Ensemble of Global and Local Classifiers for Face Recognition
In the literature of psychophysics and neurophysiology, many studies have shown that both global and local features are crucial for face representation and recognition. This paper proposes a novel face recognition method which combines both global and local discriminative features. In this method, global features are extracted from whole face images by Fourier transform and local features are extracted from some spatially partitioned image patches by Gabor wavelet transform. After this, multiple classifiers are obtained by applying Fisher Discriminant Analysis on global Fourier features and local patches of Gabor features. All these classifiers are combined to form a hierarchical ensemble by sum rule. We evaluated the proposed method using Face Recognition Grand Challenge (FRGC) experimental protocols and database known as the largest data sets available. Experimental results on FRGC version 2.0 data set have shown that the proposed method achieves a verification rate of 86%, while th...
Yu Su, Shiguang Shan, Xilin Chen, Wen Gao
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Where ICCV
Authors Yu Su, Shiguang Shan, Xilin Chen, Wen Gao
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