Improvement on null space LDA for face recognition: A symmetry consideration

Wangmeng Zuo; Kuanquan Wang; David Zhang

Improvement on null space LDA for face recognition: A symmetry consideration

Wangmeng Zuo^*
, Kuanquan Wang
, David Zhang

^*Corresponding author for this work

School of Computer Science and Technology, Harbin Institute of Technology
Hong Kong Polytechnic University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

The approximate bilateral symmetry of human face has been explored to improve the recognition performance of some face recognition algorithms such as Linear Discriminant Analysis (LDA) and Direct-LDA (D-LDA). In this paper we summary the ways to generate virtual sample using facial symmetry, and investigate the three strategies of using facial symmetric information in the Null Space LDA (NLDA) framework. The results of our experiments indicate that, the use of facial symmetric information can further improve the recognition accuracy of conventional NLDA.

Original language	English
Title of host publication	Advances in Biometrics - International Conference, ICB 2006, Proceedings
Pages	78-84
Number of pages	7
State	Published - 2006
Externally published	Yes
Event	International Conference on Biometrics, ICB 2006 - Hong Kong, China Duration: 5 Jan 2006 → 7 Jan 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3832 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Biometrics, ICB 2006
Country/Territory	China
City	Hong Kong
Period	5/01/06 → 7/01/06

Cite this

@inproceedings{2808d51921174984b532b98385932d09,

title = "Improvement on null space LDA for face recognition: A symmetry consideration",

abstract = "The approximate bilateral symmetry of human face has been explored to improve the recognition performance of some face recognition algorithms such as Linear Discriminant Analysis (LDA) and Direct-LDA (D-LDA). In this paper we summary the ways to generate virtual sample using facial symmetry, and investigate the three strategies of using facial symmetric information in the Null Space LDA (NLDA) framework. The results of our experiments indicate that, the use of facial symmetric information can further improve the recognition accuracy of conventional NLDA.",

author = "Wangmeng Zuo and Kuanquan Wang and David Zhang",

year = "2006",

language = "英语",

isbn = "3540311114",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "78--84",

booktitle = "Advances in Biometrics - International Conference, ICB 2006, Proceedings",

note = "International Conference on Biometrics, ICB 2006 ; Conference date: 05-01-2006 Through 07-01-2006",

}

Zuo, W , Wang, K & Zhang, D 2006, Improvement on null space LDA for face recognition: A symmetry consideration. in Advances in Biometrics - International Conference, ICB 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3832 LNCS, pp. 78-84, International Conference on Biometrics, ICB 2006, Hong Kong, China, 5/01/06.

Improvement on null space LDA for face recognition: A symmetry consideration. / Zuo, Wangmeng ; Wang, Kuanquan; Zhang, David.
Advances in Biometrics - International Conference, ICB 2006, Proceedings. 2006. p. 78-84 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3832 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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T2 - International Conference on Biometrics, ICB 2006

AU - Zuo, Wangmeng

AU - Wang, Kuanquan

AU - Zhang, David

PY - 2006

Y1 - 2006

N2 - The approximate bilateral symmetry of human face has been explored to improve the recognition performance of some face recognition algorithms such as Linear Discriminant Analysis (LDA) and Direct-LDA (D-LDA). In this paper we summary the ways to generate virtual sample using facial symmetry, and investigate the three strategies of using facial symmetric information in the Null Space LDA (NLDA) framework. The results of our experiments indicate that, the use of facial symmetric information can further improve the recognition accuracy of conventional NLDA.

AB - The approximate bilateral symmetry of human face has been explored to improve the recognition performance of some face recognition algorithms such as Linear Discriminant Analysis (LDA) and Direct-LDA (D-LDA). In this paper we summary the ways to generate virtual sample using facial symmetry, and investigate the three strategies of using facial symmetric information in the Null Space LDA (NLDA) framework. The results of our experiments indicate that, the use of facial symmetric information can further improve the recognition accuracy of conventional NLDA.

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M3 - 会议稿件

AN - SCOPUS:33744961214

SN - 3540311114

SN - 9783540311119

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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EP - 84

BT - Advances in Biometrics - International Conference, ICB 2006, Proceedings

Y2 - 5 January 2006 through 7 January 2006

ER -

Improvement on null space LDA for face recognition: A symmetry consideration

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