Improved-LDA based face recognition using both facial global and local information

Authors:
Dake Zhou;Xin Yang;Ningsong Peng;Yuzhong Wang
Affiliations:
Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, No. 1954 Huashan Road, Shanghai 200030, PR China;Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, No. 1954 Huashan Road, Shanghai 200030, PR China;Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, No. 1954 Huashan Road, Shanghai 200030, PR China;Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, No. 1954 Huashan Road, Shanghai 200030, PR China
Venue:
Pattern Recognition Letters
Year:
2006

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Abstract

To achieving higher classification rate under various conditions is challenging task in face recognition community. This paper presents a combined feature Fisher classifier (CF^2C) approach for face recognition, which is robust to moderate changes of illumination, pose and facial expression. The novelty of the method are: (1) the facial combined feature used for face representation, which is derived from facial global and local information extracted by DCT and (2) the development of Fisher classifier for high-dimensional multi-classes problem. Experiments on ORL and Yale face databases show that the proposed approach is superior to the traditional methods such as Eigenfaces and Fisherfaces.