DocumentCode
3102529
Title
Two-dimensional Exponential Discriminant Analysis and its Application to Face Recognition
Author
Yan, Lijun ; Pan, Jeng-Shyang
Author_Institution
Dept. of Autom. Test & Control, Harbin Inst. of Technol., Harbin, China
fYear
2010
fDate
26-28 Sept. 2010
Firstpage
528
Lastpage
531
Abstract
A novel feature extraction algorithm, named two-dimensional exponential discriminant analysis (2DEDA), is proposed in this paper. The 2DEDA is a generalization of exponential discriminant analysis (EDA). The 2DEDA is base on image matrices. So compared with the EDA, the 2DEDA has higher recognition rate and lower computational complexity. Experimental results demonstrate the advantages of 2DEDA.
Keywords
computational complexity; face recognition; feature extraction; statistical analysis; 2DEDA; computational complexity; face recognition; feature extraction algorithm; image matrices; two-dimensional exponential discriminant analysis; Algorithm design and analysis; Databases; Face; Face recognition; Feature extraction; Training; exponential discriminant analysis; face recognition; feature extraction;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Aspects of Social Networks (CASoN), 2010 International Conference on
Conference_Location
Taiyuan
Print_ISBN
978-1-4244-8785-1
Type
conf
DOI
10.1109/CASoN.2010.123
Filename
5636651
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