Neighborhood Discriminant Nearest Feature Line Analysis for Face Recognition

Lijun Yan, Shu-Chuan Chu, Jeng-Shyang Pan, John Roddick

    Research output: Contribution to conferencePaper

    18 Citations (Scopus)

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

    Original languageEnglish
    Pages344-347
    Number of pages4
    DOIs
    Publication statusPublished - 1 Dec 2011
    Event2nd International Conference on Innovations in Bio-inspired Computing and Applications -
    Duration: 16 Dec 2011 → …

    Conference

    Conference2nd International Conference on Innovations in Bio-inspired Computing and Applications
    Period16/12/11 → …

    Keywords

    • face
    • Nearest feature line
    • subspace learning

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