Title: Improved-LDA based face recognition using both facial global and local information
Abstract: To achieving higher classification rate under various conditions is challenging task in face recognition community. This paper presents a combined feature Fisher classifier (CF2C) 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.
Publication Year: 2005
Publication Date: 2005-10-26
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 41
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