Neighborhood Discriminant Nearest Feature Line Analysis for Face Recognition

Authors:
Lijun Yan;Jeng-Shyang Pan;Shu-Chuan Chu;John F. Roddick
Affiliations:
-;-;-;-
Venue:
IBICA '11 Proceedings of the 2011 Second International Conference on Innovations in Bio-inspired Computing and Applications
Year:
2011

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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.聽聽At the same time, theneighborhood is preserved in the feature space. Experimental results demonstrate the efficiency of the proposed algorithm.