DocumentCode
2863337
Title
Neighborhood Discriminant Nearest Feature Line Analysis for Face Recognition
Author
Yan, Lijun ; Pan, Jeng-Shyang ; Chu, Shu-Chuan ; Roddick, John F.
Author_Institution
Dept. of Autom. Test & Control, Harbin Inst. of Technol., Harbin, China
fYear
2011
fDate
16-18 Dec. 2011
Firstpage
344
Lastpage
347
Abstract
A novel subspace learning algorithm named neighborhood discriminant nearest feature line analysis (NDNFLA) is proposed in this paper. NDNFLA aims to find the discriminant feature of samples by maximizing the between-class feature line (FL) distances and minimizing the within-class FL distance. At the same time, the neighborhood is preserved in the feature space. Experimental results demonstrate the efficiency of the proposed algorithm.
Keywords
face recognition; learning (artificial intelligence); NDNFLA; between-class feature line; face recognition; neighborhood discriminant nearest feature line analysis; subspace learning algorithm; within-class FL distance; Algorithm design and analysis; Face; Face recognition; Feature extraction; Kernel; Principal component analysis; Training; Nearest feature line; face; subspace learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovations in Bio-inspired Computing and Applications (IBICA), 2011 Second International Conference on
Conference_Location
Shenzhan
Print_ISBN
978-1-4577-1219-7
Type
conf
DOI
10.1109/IBICA.2011.91
Filename
6118775
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