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
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;
Conference_Titel :
Computational Aspects of Social Networks (CASoN), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-8785-1
DOI :
10.1109/CASoN.2010.123
