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
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;
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
DOI :
10.1109/IBICA.2011.91
