Improvements on the linear discrimination technique with application to face recognition

Xiao Yuan Jing; Dapeng Zhang; Yong Fang Yao

doi:10.1016/S0167-8655(03)00112-0

Improvements on the linear discrimination technique with application to face recognition

Xiao Yuan Jing, Dapeng Zhang, Yong Fang Yao

Research output: Journal article publication › Journal article › Academic research › peer-review

20 Citations (Scopus)

Abstract

In this paper, new improvements for the linear discrimination technique are proposed. These improvements include effective solutions for the small sample size problem, the selection of appropriate principal component and more accurate within-class scatter estimation for the Fisher criterion. The effectiveness of our approach is proved by experimental results on the Yale face database.

Original language	English
Pages (from-to)	2695-2701
Number of pages	7
Journal	Pattern Recognition Letters
Volume	24
Issue number	15
DOIs	https://doi.org/10.1016/S0167-8655(03)00112-0
Publication status	Published - 1 Jan 2003

Keywords

Face recognition
Linear discrimination
Principal component selection
Small sample size problem
Within-class scatter estimation

ASJC Scopus subject areas

Software
Signal Processing
Computer Vision and Pattern Recognition
Artificial Intelligence

More information

10.1016/S0167-8655(03)00112-0

Cite this

@article{518d684dd72940eaaf6bfd0e0b7fbaeb,

title = "Improvements on the linear discrimination technique with application to face recognition",

abstract = "In this paper, new improvements for the linear discrimination technique are proposed. These improvements include effective solutions for the small sample size problem, the selection of appropriate principal component and more accurate within-class scatter estimation for the Fisher criterion. The effectiveness of our approach is proved by experimental results on the Yale face database.",

keywords = "Face recognition, Linear discrimination, Principal component selection, Small sample size problem, Within-class scatter estimation",

author = "Jing, {Xiao Yuan} and Dapeng Zhang and Yao, {Yong Fang}",

year = "2003",

month = jan,

day = "1",

doi = "10.1016/S0167-8655(03)00112-0",

language = "English",

volume = "24",

pages = "2695--2701",

journal = "Pattern Recognition Letters",

issn = "0167-8655",

publisher = "Elsevier B.V.",

number = "15",

}

TY - JOUR

T1 - Improvements on the linear discrimination technique with application to face recognition

AU - Jing, Xiao Yuan

AU - Zhang, Dapeng

AU - Yao, Yong Fang

PY - 2003/1/1

Y1 - 2003/1/1

N2 - In this paper, new improvements for the linear discrimination technique are proposed. These improvements include effective solutions for the small sample size problem, the selection of appropriate principal component and more accurate within-class scatter estimation for the Fisher criterion. The effectiveness of our approach is proved by experimental results on the Yale face database.

AB - In this paper, new improvements for the linear discrimination technique are proposed. These improvements include effective solutions for the small sample size problem, the selection of appropriate principal component and more accurate within-class scatter estimation for the Fisher criterion. The effectiveness of our approach is proved by experimental results on the Yale face database.

KW - Face recognition

KW - Linear discrimination

KW - Principal component selection

KW - Small sample size problem

KW - Within-class scatter estimation

UR - http://www.scopus.com/inward/record.url?scp=0042830878&partnerID=8YFLogxK

U2 - 10.1016/S0167-8655(03)00112-0

DO - 10.1016/S0167-8655(03)00112-0

M3 - Journal article

SN - 0167-8655

VL - 24

SP - 2695

EP - 2701

JO - Pattern Recognition Letters

JF - Pattern Recognition Letters

IS - 15

ER -

Improvements on the linear discrimination technique with application to face recognition

Abstract

Keywords

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this