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| A novel face recognition method with feature combination |
| LI Wen-shu, ZHOU Chang-le, XU Jia-tuo |
| School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China; College of Information and Electronics, Zhejiang Sci-Tech University, Hangzhou 310018, China; Department of Artificial Intelligence, Xiamen University, Xiamen 361005, China; Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China |
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Abstract A novel combined personalized feature framework is proposed for face recognition (FR). In the framework, the proposed linear discriminant analysis (LDA) makes use of the null space of the within-class scatter matrix effectively, and Global feature vectors (PCA-transformed) and local feature vectors (Gabor wavelet-transformed) are integrated by complex vectors as input feature of improved LDA. The proposed method is compared to other commonly used FR methods on two face databases (ORL and UMIST). Results demonstrated that the performance of the proposed method is superior to that of traditional FR approaches
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Received: 27 January 2004
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