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An analytical algorithm for determining the generalized optimal set of discriminant vectors |
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| Authors: | Wu Xiao-Jun [Author Vitae] Josef Kittler [Author Vitae] [Author Vitae] Wang Shi-Tong [Author Vitae] |
| Affiliation: | a School of Electronics and Information, East China Shipbuilding Institute, No. 2 Huancheng Road, Zhenjiang 212003, China b Robotics Laboratory, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110015, China c CVSSP, University of Surrey, Surrey GU2 7XH, UK d School of Information, Nanjing University of Science & Technology, Nanjing 210094, China |
| Abstract: | Generalized linear discriminant analysis has been successfully used as a dimensionality reduction technique in many classification tasks. An analytical method for finding the optimal set of generalized discriminant vectors is proposed in this paper. Compared with other methods, the proposed method has the advantage of requiring less computational time and achieving higher recognition rates. The results of experiments conducted on the Olivetti Research Lab facial database show the effectiveness of the proposed method. |
| Keywords: | Feature extraction Generalized optimal discriminant vectors Face recognition LDA |
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