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

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

doi:10.6138/JIT.2013.14.1.13

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 journal › Article › peer-review

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 language	English
Pages (from-to)	127-132
Number of pages	6
Journal	Journal of Internet Technology
Volume	14
Issue number	1
DOIs	https://doi.org/10.6138/JIT.2013.14.1.13
Publication status	Published - 2013

Keywords

Feature extraction
Nearest feature line
Subspace learning

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10.6138/JIT.2013.14.1.13

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KW - Subspace learning

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