Multiple feature point discriminant analysis and its application to feature extraction

Lijun Yan; Junbao Li; Ying Zhou

doi:10.1145/3362752.3365198

Multiple feature point discriminant analysis and its application to feature extraction

Lijun Yan
, Junbao Li
, Ying Zhou

Faculty of Computing

Shenzhen Institute of Information Technology

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

Abstract

In this paper, a novel linear subspace learning approach, named Multiple Feature Point Discriminant Analysis (MFPDA), is proposed. MFPDA is in order to maximize the multiple feature point between class scatter and minimize the multiple feature point within-class scatter. Some experiments are performed on FKP database, AR face database, and ORL face database to evaluate the effectiveness of the proposed MFPDA. Compared with some popular subspace learning methods, such as PCA, LDA, LLP, UNDFLA, JSPCA, the proposed MFPDA has highest average recognition accuracy. The experimental results confirm the effectiveness of the proposed algorithm.

Original language	English
Title of host publication	Proceedings of 2019 2nd International Conference on Electronics and Electrical Engineering Technology, EEET 2019 - Workshop 2019 3rd International Conference on Biomedical Engineering and Bioinformatics, ICBEB 2019
Publisher	Association for Computing Machinery
Pages	19-23
Number of pages	5
ISBN (Electronic)	9781450372145
DOIs	https://doi.org/10.1145/3362752.3365198
State	Published - 25 Sep 2019
Event	2nd International Conference on Electronics and Electrical Engineering Technology, EEET 2019 and its Workshop 2019 3rd International Conference on Biomedical Engineering and Bioinformatics, ICBEB 2019 - Penang, Malaysia Duration: 25 Sep 2019 → 27 Sep 2019

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	2nd International Conference on Electronics and Electrical Engineering Technology, EEET 2019 and its Workshop 2019 3rd International Conference on Biomedical Engineering and Bioinformatics, ICBEB 2019
Country/Territory	Malaysia
City	Penang
Period	25/09/19 → 27/09/19

Keywords

Feature line
Feature plane
Feature space
Subspace learning

Access to Document

10.1145/3362752.3365198

Cite this

Yan, L., Li, J., & Zhou, Y. (2019). Multiple feature point discriminant analysis and its application to feature extraction. In Proceedings of 2019 2nd International Conference on Electronics and Electrical Engineering Technology, EEET 2019 - Workshop 2019 3rd International Conference on Biomedical Engineering and Bioinformatics, ICBEB 2019 (pp. 19-23). (ACM International Conference Proceeding Series). Association for Computing Machinery . https://doi.org/10.1145/3362752.3365198

Yan, Lijun ; Li, Junbao ; Zhou, Ying. / Multiple feature point discriminant analysis and its application to feature extraction. Proceedings of 2019 2nd International Conference on Electronics and Electrical Engineering Technology, EEET 2019 - Workshop 2019 3rd International Conference on Biomedical Engineering and Bioinformatics, ICBEB 2019. Association for Computing Machinery , 2019. pp. 19-23 (ACM International Conference Proceeding Series).

@inproceedings{c8731044fabe464ba72f7a97817f21df,

title = "Multiple feature point discriminant analysis and its application to feature extraction",

abstract = "In this paper, a novel linear subspace learning approach, named Multiple Feature Point Discriminant Analysis (MFPDA), is proposed. MFPDA is in order to maximize the multiple feature point between class scatter and minimize the multiple feature point within-class scatter. Some experiments are performed on FKP database, AR face database, and ORL face database to evaluate the effectiveness of the proposed MFPDA. Compared with some popular subspace learning methods, such as PCA, LDA, LLP, UNDFLA, JSPCA, the proposed MFPDA has highest average recognition accuracy. The experimental results confirm the effectiveness of the proposed algorithm.",

keywords = "Feature line, Feature plane, Feature space, Subspace learning",

author = "Lijun Yan and Junbao Li and Ying Zhou",

note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 2nd International Conference on Electronics and Electrical Engineering Technology, EEET 2019 and its Workshop 2019 3rd International Conference on Biomedical Engineering and Bioinformatics, ICBEB 2019 ; Conference date: 25-09-2019 Through 27-09-2019",

year = "2019",

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doi = "10.1145/3362752.3365198",

language = "英语",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery ",

pages = "19--23",

booktitle = "Proceedings of 2019 2nd International Conference on Electronics and Electrical Engineering Technology, EEET 2019 - Workshop 2019 3rd International Conference on Biomedical Engineering and Bioinformatics, ICBEB 2019",

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Yan, L, Li, J & Zhou, Y 2019, Multiple feature point discriminant analysis and its application to feature extraction. in Proceedings of 2019 2nd International Conference on Electronics and Electrical Engineering Technology, EEET 2019 - Workshop 2019 3rd International Conference on Biomedical Engineering and Bioinformatics, ICBEB 2019. ACM International Conference Proceeding Series, Association for Computing Machinery , pp. 19-23, 2nd International Conference on Electronics and Electrical Engineering Technology, EEET 2019 and its Workshop 2019 3rd International Conference on Biomedical Engineering and Bioinformatics, ICBEB 2019, Penang, Malaysia, 25/09/19. https://doi.org/10.1145/3362752.3365198

Multiple feature point discriminant analysis and its application to feature extraction. / Yan, Lijun; Li, Junbao; Zhou, Ying.
Proceedings of 2019 2nd International Conference on Electronics and Electrical Engineering Technology, EEET 2019 - Workshop 2019 3rd International Conference on Biomedical Engineering and Bioinformatics, ICBEB 2019. Association for Computing Machinery , 2019. p. 19-23 (ACM International Conference Proceeding Series).

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

TY - GEN

T1 - Multiple feature point discriminant analysis and its application to feature extraction

AU - Yan, Lijun

AU - Li, Junbao

AU - Zhou, Ying

PY - 2019/9/25

Y1 - 2019/9/25

N2 - In this paper, a novel linear subspace learning approach, named Multiple Feature Point Discriminant Analysis (MFPDA), is proposed. MFPDA is in order to maximize the multiple feature point between class scatter and minimize the multiple feature point within-class scatter. Some experiments are performed on FKP database, AR face database, and ORL face database to evaluate the effectiveness of the proposed MFPDA. Compared with some popular subspace learning methods, such as PCA, LDA, LLP, UNDFLA, JSPCA, the proposed MFPDA has highest average recognition accuracy. The experimental results confirm the effectiveness of the proposed algorithm.

AB - In this paper, a novel linear subspace learning approach, named Multiple Feature Point Discriminant Analysis (MFPDA), is proposed. MFPDA is in order to maximize the multiple feature point between class scatter and minimize the multiple feature point within-class scatter. Some experiments are performed on FKP database, AR face database, and ORL face database to evaluate the effectiveness of the proposed MFPDA. Compared with some popular subspace learning methods, such as PCA, LDA, LLP, UNDFLA, JSPCA, the proposed MFPDA has highest average recognition accuracy. The experimental results confirm the effectiveness of the proposed algorithm.

KW - Feature line

KW - Feature plane

KW - Feature space

KW - Subspace learning

UR - https://www.scopus.com/pages/publications/85077692261

U2 - 10.1145/3362752.3365198

DO - 10.1145/3362752.3365198

M3 - 会议稿件

AN - SCOPUS:85077692261

T3 - ACM International Conference Proceeding Series

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BT - Proceedings of 2019 2nd International Conference on Electronics and Electrical Engineering Technology, EEET 2019 - Workshop 2019 3rd International Conference on Biomedical Engineering and Bioinformatics, ICBEB 2019

PB - Association for Computing Machinery

T2 - 2nd International Conference on Electronics and Electrical Engineering Technology, EEET 2019 and its Workshop 2019 3rd International Conference on Biomedical Engineering and Bioinformatics, ICBEB 2019

Y2 - 25 September 2019 through 27 September 2019

ER -

Yan L, Li J, Zhou Y. Multiple feature point discriminant analysis and its application to feature extraction. In Proceedings of 2019 2nd International Conference on Electronics and Electrical Engineering Technology, EEET 2019 - Workshop 2019 3rd International Conference on Biomedical Engineering and Bioinformatics, ICBEB 2019. Association for Computing Machinery . 2019. p. 19-23. (ACM International Conference Proceeding Series). doi: 10.1145/3362752.3365198

Multiple feature point discriminant analysis and its application to feature extraction

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