Two-dimensional FLD for face recognition

被引：164

作者：

Xiong, HL ^{[1
]}

Swamy, MNS ^{[1
]}

Ahmad, MO ^{[1
]}

机构：

[1] Concordia Univ, Dept Elect & Comp Engn, Montreal, PQ H3G 1M8, Canada

来源：

PATTERN RECOGNITION | 2005年 / 38卷 / 07期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Fisher criterion; principal component analysis (PCA); linear discriminant analysis (LDA);

D O I：

10.1016/j.patcog.2004.12.003

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a new scheme of face image feature extraction, namely, the two-dimensional Fisher linear discriminant. Experiments on the ORL and the UMIST face databases show that the new scheme outperforms the PCA and the conventional PICA + FLD schemes, not only in its computational efficiency, but also in its performance for the task of face recognition. (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

引用

页码：1121 / 1124

页数：4

共 5 条

[1] Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection
Belhumeur, PN
Hespanha, JP
Kriegman, DJ
[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1997, 19 (07) : 711 - 720
[2] A new LDA-based face recognition system which can solve the small sample size problem
Chen, LF
Liao, HYM
Ko, MT
Lin, JC
Yu, GJ
[J]. PATTERN RECOGNITION, 2000, 33 (10) : 1713 - 1726
[3] Fukunaga K., 1990, INTRO STAT PATTERN R
[4] Two-dimensional PCA: A new approach to appearance-based face representation and recognition
Yang, J
Zhang, D
Frangi, AF
Yang, JY
[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2004, 26 (01) : 131 - 137
[5] A direct LDA algorithm for high-dimensional data - with application to face recognition
Yu, H
Yang, H
[J]. PATTERN RECOGNITION, 2001, 34 (10) : 2067 - 2070

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