Neighborhood Discriminant Nearest Feature Line Analysis and Its Application to Face Recognition

Lijun Yan, Weimin Zheng, Shu-Chuan Chu, John Roddick

    Research output: Contribution to journalArticle

    3 Citations (Scopus)

    Abstract

    In this paper, a novel subspace learning algorithm, called neighborhood discriminant nearest feature line analysis (NDNFLA), is proposed. NDNFLA aims to find the discriminant feature of samples by maximizing the between-class feature line (FL) scatter and minimizing the within-class FL scatter. At the same time, the neighborhood is preserved in the feature space. Experimental results demonstrate the efficiency of the proposed algorithm.

    Original languageEnglish
    Pages (from-to)127-132
    Number of pages6
    JournalJournal of Internet Technology
    Volume14
    Issue number1
    DOIs
    Publication statusPublished - 2013

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