Nonlinear DCT Discriminant Feature Extraction with Generalized KDCV for Face Recognition

Authors:
Sheng Li;Yong-fang Yao;Xiao-yuan Jing;Zhu-li Shao;David Zhang;Jing-yu Yang
Affiliations:
-;-;-;-;-;-
Venue:
IITA '08 Proceedings of the 2008 Second International Symposium on Intelligent Information Technology Application - Volume 03
Year:
2008

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A Gabor-block-based kernel discriminative common vector approach using cosine kernels for human face recognition

Computational Intelligence and Neuroscience

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Abstract

A nonlinear DCT discriminant feature extraction approach for face recognition is proposed. First, we analyze the nonlinear discriminabilities of DCT frequency bands and select appropriate bands. Second, we extract nonlinear discriminant features from the selected DCT bands by presenting a new kernel discriminant method, i.e. generalized kernel discriminative common vector (KDCV) method. The experimental results on the Feret database demonstrate the effectiveness of this new approach.