A novel dictionary based SRC for face recognition

Ying Wen

doi:10.1109/ICASSP.2017.7952623

A novel dictionary based SRC for face recognition

Ying Wen^*

^*Corresponding author for this work

School of Communication and Electronic Engineering

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

9 Scopus citations

Abstract

The sparse representation based classification (SRC) performs not very well for small sample data. A discriminative common vector dictionary based SRC is introduced in this paper to address this issue. The contribution of this paper is that the dictionary of the proposed method is constructed by the discriminative common vector per class. The common vector represents the invariant property of each class, which is helpful to improve the performance of the proposed method for small sample database. Furthermore, the new dictionary has much less atoms than the original SRC based scheme, which reduces the computational cost. The experiments implemented on ORL, AR and LFW face databases demonstrate the effectiveness of the proposed method.

Original language	English
Title of host publication	2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2582-2586
Number of pages	5
ISBN (Electronic)	9781509041176
DOIs	https://doi.org/10.1109/ICASSP.2017.7952623
State	Published - 16 Jun 2017
Event	2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - New Orleans, United States Duration: 5 Mar 2017 → 9 Mar 2017

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)	1520-6149

Conference

Conference	2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
Country/Territory	United States
City	New Orleans
Period	5/03/17 → 9/03/17

Keywords

Sparse representation classification
discriminative common vector
face recognition

Access to Document

10.1109/ICASSP.2017.7952623

Cite this

Wen, Y. (2017). A novel dictionary based SRC for face recognition. In 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings (pp. 2582-2586). Article 7952623 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2017.7952623

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title = "A novel dictionary based SRC for face recognition",

abstract = "The sparse representation based classification (SRC) performs not very well for small sample data. A discriminative common vector dictionary based SRC is introduced in this paper to address this issue. The contribution of this paper is that the dictionary of the proposed method is constructed by the discriminative common vector per class. The common vector represents the invariant property of each class, which is helpful to improve the performance of the proposed method for small sample database. Furthermore, the new dictionary has much less atoms than the original SRC based scheme, which reduces the computational cost. The experiments implemented on ORL, AR and LFW face databases demonstrate the effectiveness of the proposed method.",

keywords = "Sparse representation classification, discriminative common vector, face recognition",

author = "Ying Wen",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 ; Conference date: 05-03-2017 Through 09-03-2017",

year = "2017",

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doi = "10.1109/ICASSP.2017.7952623",

language = "英语",

series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

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Wen, Y 2017, A novel dictionary based SRC for face recognition. in 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings., 7952623, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 2582-2586, 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017, New Orleans, United States, 5/03/17. https://doi.org/10.1109/ICASSP.2017.7952623

A novel dictionary based SRC for face recognition. / Wen, Ying.
2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 2582-2586 7952623 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

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

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N2 - The sparse representation based classification (SRC) performs not very well for small sample data. A discriminative common vector dictionary based SRC is introduced in this paper to address this issue. The contribution of this paper is that the dictionary of the proposed method is constructed by the discriminative common vector per class. The common vector represents the invariant property of each class, which is helpful to improve the performance of the proposed method for small sample database. Furthermore, the new dictionary has much less atoms than the original SRC based scheme, which reduces the computational cost. The experiments implemented on ORL, AR and LFW face databases demonstrate the effectiveness of the proposed method.

AB - The sparse representation based classification (SRC) performs not very well for small sample data. A discriminative common vector dictionary based SRC is introduced in this paper to address this issue. The contribution of this paper is that the dictionary of the proposed method is constructed by the discriminative common vector per class. The common vector represents the invariant property of each class, which is helpful to improve the performance of the proposed method for small sample database. Furthermore, the new dictionary has much less atoms than the original SRC based scheme, which reduces the computational cost. The experiments implemented on ORL, AR and LFW face databases demonstrate the effectiveness of the proposed method.

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KW - discriminative common vector

KW - face recognition

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BT - 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017

Y2 - 5 March 2017 through 9 March 2017

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Wen Y. A novel dictionary based SRC for face recognition. In 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 2582-2586. 7952623. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/ICASSP.2017.7952623

A novel dictionary based SRC for face recognition

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