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ICANN
2005
Springer

Discriminative Common Images for Face Recognition

14 years 1 months ago
Discriminative Common Images for Face Recognition
Linear discrimination analysis (LDA) technique is an important and well-developed area of image recognition and to date many linear discrimination methods have been put forward. Basically, in LDA the image always needs to be transformed into 1D vector, however recently twodimensional PCA (2DPCA) technique have been proposed. In 2DPCA, PCA technique is applied directly on the original images without transforming into 1D vector. In this paper, we propose a new LDA-based method that applies the idea of two-dimensional PCA. In addition to that, our approach proposes an method called Discriminative Common Images based on a variation of Fisher’s LDA for face recognition. Experiment results show our method achieves better performance in comparison with the other traditional LDA methods.
Vo Dinh Minh Nhat, Sungyoung Lee
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where ICANN
Authors Vo Dinh Minh Nhat, Sungyoung Lee
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