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

Access to Document

10.6138/JIT.2013.14.1.13

Cite this

@article{b35b1796a00348f8bfa097f659d54f0b,

title = "Neighborhood Discriminant Nearest Feature Line Analysis and Its Application to Face Recognition",

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.",

keywords = "Feature extraction, Nearest feature line, Subspace learning",

author = "Lijun Yan and Weimin Zheng and Shu-Chuan Chu and John Roddick",

year = "2013",

doi = "10.6138/JIT.2013.14.1.13",

language = "English",

volume = "14",

pages = "127--132",

journal = "Journal of Internet Technology",

issn = "1607-9264",

publisher = "Taiwan Academic Network Management Committee",

number = "1",

}

TY - JOUR

T1 - Neighborhood Discriminant Nearest Feature Line Analysis and Its Application to Face Recognition

AU - Yan, Lijun

AU - Zheng, Weimin

AU - Chu, Shu-Chuan

AU - Roddick, John

PY - 2013

Y1 - 2013

N2 - 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.

AB - 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.

KW - Feature extraction

KW - Nearest feature line

KW - Subspace learning

UR - http://www.scopus.com/inward/record.url?scp=84883097307&partnerID=8YFLogxK

U2 - 10.6138/JIT.2013.14.1.13

DO - 10.6138/JIT.2013.14.1.13

M3 - Article

SN - 1607-9264

VL - 14

SP - 127

EP - 132

JO - Journal of Internet Technology

JF - Journal of Internet Technology

IS - 1

ER -

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

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this