DocumentCode :
495492
Title :
Uncorrelated Discriminant Locality Aware Embedding for Face Recognition
Author :
Songjiang, Lou ; Guoyin, Zhang ; Qingjun, Wang
Author_Institution :
Dept. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin, China
Volume :
4
fYear :
2009
fDate :
March 31 2009-April 2 2009
Firstpage :
178
Lastpage :
181
Abstract :
In this paper, we describe a feature extraction algorithm called discriminant uncorrelated locality aware embedding, DULAM for short, which is based on LPP (locality preserving projection). LPP can preserve the local structure of the data, but does not take the class information into account, besides, the extracted feature might be highly correlated. To overcome these drawbacks, DULAM is proposed, which not only preserves the locality of the data, but also takes the class information into consideration, and an uncorrelated constraint is also imposed to reduce the redundancy, thus it betters the recognition performance. Experiments validate the correctness and effectiveness of the algorithm.
Keywords :
face recognition; feature extraction; learning (artificial intelligence); data local structure; face recognition; feature extraction algorithm; locality preserving projection; uncorrelated discriminant locality aware embedding; Computer science; Data mining; Face recognition; Feature extraction; Helium; Linear discriminant analysis; Nearest neighbor searches; Principal component analysis; Scattering; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
Type :
conf
DOI :
10.1109/CSIE.2009.555
Filename :
5170983
Link To Document :
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