Multilinear local fisher discriminant analysis for face recognition

Yucong Peng; Peng Zhou; Hao Zheng; Baochang Zhang; Wankou Yang

doi:10.1007/978-3-319-46654-5_15

Multilinear local fisher discriminant analysis for face recognition

Yucong Peng
, Peng Zhou
, Hao Zheng
, Baochang Zhang
, Wankou Yang^*

^*此作品的通讯作者

人工智能学院(人工智能研究院)

Southeast University, Nanjing
Key Laboratory of Precision Opto-Mechatronics Technology (Ministry of Education)
Nanjing Xiaozhuang College

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

1 引用（Scopus）

摘要

In this paper, a multilinear local fisher discriminant analysis (MLFDA) framework is introduced for tensor object dimensionality reduction and recognition. MLFDA achieves feature extraction by finding a multilinear projection to map the original tensor space into a tensor subspace that maximize the local between-class scatter as well as minimize the local within-class scatter. The experimental result shows that MLFDA has an outperformance.

源语言	英语
主期刊名	Biometric Recognition - 11th Chinese Conference, CCBR 2016, Proceedings
编辑	Shiguang Shan, Zhisheng You, Jie Zhou, Weishi Zheng, Yunhong Wang, Zhenan Sun, Jianjiang Feng, Qijun Zhao
出版商	Springer Verlag
页	130-138
页数	9
ISBN（印刷版）	9783319466538
DOI	https://doi.org/10.1007/978-3-319-46654-5_15
出版状态	已出版 - 2016
活动	11th Chinese Conference on Biometric Recognition, CCBR 2016 - Chengdu, 中国期限: 14 10月 2016 → 16 10月 2016

出版系列

姓名	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	9967 LNCS
ISSN（印刷版）	0302-9743
ISSN（电子版）	1611-3349

会议

会议	11th Chinese Conference on Biometric Recognition, CCBR 2016
国家/地区	中国
市	Chengdu
时期	14/10/16 → 16/10/16

访问文件

10.1007/978-3-319-46654-5_15

其它文件与链接

链接到 Scopus 的出版物

引用此

Peng, Y., Zhou, P., Zheng, H., Zhang, B., & Yang, W. (2016). Multilinear local fisher discriminant analysis for face recognition. 在 S. Shan, Z. You, J. Zhou, W. Zheng, Y. Wang, Z. Sun, J. Feng, & Q. Zhao (编辑), Biometric Recognition - 11th Chinese Conference, CCBR 2016, Proceedings (页码 130-138). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 9967 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46654-5_15

Peng, Yucong ; Zhou, Peng ; Zheng, Hao 等. / Multilinear local fisher discriminant analysis for face recognition. Biometric Recognition - 11th Chinese Conference, CCBR 2016, Proceedings. 编辑 / Shiguang Shan ; Zhisheng You ; Jie Zhou ; Weishi Zheng ; Yunhong Wang ; Zhenan Sun ; Jianjiang Feng ; Qijun Zhao. Springer Verlag, 2016. 页码 130-138 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{e9efadb82d2c46d6b6e69b47e765a412,

title = "Multilinear local fisher discriminant analysis for face recognition",

abstract = "In this paper, a multilinear local fisher discriminant analysis (MLFDA) framework is introduced for tensor object dimensionality reduction and recognition. MLFDA achieves feature extraction by finding a multilinear projection to map the original tensor space into a tensor subspace that maximize the local between-class scatter as well as minimize the local within-class scatter. The experimental result shows that MLFDA has an outperformance.",

keywords = "Dimensionalityk reduction, Face recognition, Local fisher discriminant analysis (LFDA), Tensor",

author = "Yucong Peng and Peng Zhou and Hao Zheng and Baochang Zhang and Wankou Yang",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 11th Chinese Conference on Biometric Recognition, CCBR 2016 ; Conference date: 14-10-2016 Through 16-10-2016",

year = "2016",

doi = "10.1007/978-3-319-46654-5\_15",

language = "英语",

isbn = "9783319466538",

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

publisher = "Springer Verlag",

pages = "130--138",

editor = "Shiguang Shan and Zhisheng You and Jie Zhou and Weishi Zheng and Yunhong Wang and Zhenan Sun and Jianjiang Feng and Qijun Zhao",

booktitle = "Biometric Recognition - 11th Chinese Conference, CCBR 2016, Proceedings",

address = "德国",

}

Peng, Y, Zhou, P, Zheng, H, Zhang, B & Yang, W 2016, Multilinear local fisher discriminant analysis for face recognition. 在 S Shan, Z You, J Zhou, W Zheng, Y Wang, Z Sun, J Feng & Q Zhao (编辑), Biometric Recognition - 11th Chinese Conference, CCBR 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 9967 LNCS, Springer Verlag, 页码 130-138, 11th Chinese Conference on Biometric Recognition, CCBR 2016, Chengdu, 中国, 14/10/16. https://doi.org/10.1007/978-3-319-46654-5_15

Multilinear local fisher discriminant analysis for face recognition. / Peng, Yucong; Zhou, Peng; Zheng, Hao 等.
Biometric Recognition - 11th Chinese Conference, CCBR 2016, Proceedings. 编辑 / Shiguang Shan; Zhisheng You; Jie Zhou; Weishi Zheng; Yunhong Wang; Zhenan Sun; Jianjiang Feng; Qijun Zhao. Springer Verlag, 2016. 页码 130-138 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 9967 LNCS).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Multilinear local fisher discriminant analysis for face recognition

AU - Peng, Yucong

AU - Zhou, Peng

AU - Zheng, Hao

AU - Zhang, Baochang

AU - Yang, Wankou

N1 - Publisher Copyright: © Springer International Publishing AG 2016.

PY - 2016

Y1 - 2016

N2 - In this paper, a multilinear local fisher discriminant analysis (MLFDA) framework is introduced for tensor object dimensionality reduction and recognition. MLFDA achieves feature extraction by finding a multilinear projection to map the original tensor space into a tensor subspace that maximize the local between-class scatter as well as minimize the local within-class scatter. The experimental result shows that MLFDA has an outperformance.

AB - In this paper, a multilinear local fisher discriminant analysis (MLFDA) framework is introduced for tensor object dimensionality reduction and recognition. MLFDA achieves feature extraction by finding a multilinear projection to map the original tensor space into a tensor subspace that maximize the local between-class scatter as well as minimize the local within-class scatter. The experimental result shows that MLFDA has an outperformance.

KW - Dimensionalityk reduction

KW - Face recognition

KW - Local fisher discriminant analysis (LFDA)

KW - Tensor

UR - https://www.scopus.com/pages/publications/84992458922

U2 - 10.1007/978-3-319-46654-5_15

DO - 10.1007/978-3-319-46654-5_15

M3 - 会议稿件

AN - SCOPUS:84992458922

SN - 9783319466538

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

SP - 130

EP - 138

BT - Biometric Recognition - 11th Chinese Conference, CCBR 2016, Proceedings

A2 - Shan, Shiguang

A2 - You, Zhisheng

A2 - Zhou, Jie

A2 - Zheng, Weishi

A2 - Wang, Yunhong

A2 - Sun, Zhenan

A2 - Feng, Jianjiang

A2 - Zhao, Qijun

PB - Springer Verlag

T2 - 11th Chinese Conference on Biometric Recognition, CCBR 2016

Y2 - 14 October 2016 through 16 October 2016

ER -

Peng Y, Zhou P, Zheng H, Zhang B, Yang W. Multilinear local fisher discriminant analysis for face recognition. 在 Shan S, You Z, Zhou J, Zheng W, Wang Y, Sun Z, Feng J, Zhao Q, 编辑, Biometric Recognition - 11th Chinese Conference, CCBR 2016, Proceedings. Springer Verlag. 2016. 页码 130-138. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-46654-5_15

Multilinear local fisher discriminant analysis for face recognition

摘要

出版系列

会议

访问文件

其它文件与链接

学术指纹

引用此