Face gender recognition based on 2D principal component analysis and support vector machine

Research output: A Conference proceeding or a Chapter in BookConference contribution

9 Citations (Scopus)

Abstract

This paper presents a novel method for solving face gender recognition problem. This method employs 2D Principal Component Analysis, one of the prominent methods for extracting feature vectors, and Support Vector Machine, the most powerful discriminative method for classification. Experiments for the proposed approach have been conducted on FERET data set and the results show that the proposed method could improve the classification rates.
Original languageEnglish
Title of host publication2010 Fourth International Conference on Network and System Security: NSS 2010
EditorsYang Xiang, Pierangela Samarati, Jiankun Hu, Wanlei Zhou, Ahmad-Reza Sadeghi
Place of PublicationPiscataway, N.J., USA
PublisherIEEE
Pages579-582
Number of pages4
ISBN (Print)9781424484843
DOIs
Publication statusPublished - 2010
EventFourth International Conference on Network and System Security (NSS 2010), - Melbourne, Australia
Duration: 1 Sep 20103 Sep 2010

Conference

ConferenceFourth International Conference on Network and System Security (NSS 2010),
CountryAustralia
CityMelbourne
Period1/09/103/09/10

Fingerprint

Face recognition
Principal component analysis
Support vector machines
Experiments

Cite this

Tran, D., Huang, X., & Chetty, G. (2010). Face gender recognition based on 2D principal component analysis and support vector machine. In Y. Xiang, P. Samarati, J. Hu, W. Zhou, & A-R. Sadeghi (Eds.), 2010 Fourth International Conference on Network and System Security: NSS 2010 (pp. 579-582). Piscataway, N.J., USA: IEEE. https://doi.org/10.1109/NSS.2010.19
Tran, Dat ; Huang, Xu ; Chetty, Girija. / Face gender recognition based on 2D principal component analysis and support vector machine. 2010 Fourth International Conference on Network and System Security: NSS 2010. editor / Yang Xiang ; Pierangela Samarati ; Jiankun Hu ; Wanlei Zhou ; Ahmad-Reza Sadeghi. Piscataway, N.J., USA : IEEE, 2010. pp. 579-582
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title = "Face gender recognition based on 2D principal component analysis and support vector machine",
abstract = "This paper presents a novel method for solving face gender recognition problem. This method employs 2D Principal Component Analysis, one of the prominent methods for extracting feature vectors, and Support Vector Machine, the most powerful discriminative method for classification. Experiments for the proposed approach have been conducted on FERET data set and the results show that the proposed method could improve the classification rates.",
author = "Dat Tran and Xu Huang and Girija Chetty",
year = "2010",
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Tran, D, Huang, X & Chetty, G 2010, Face gender recognition based on 2D principal component analysis and support vector machine. in Y Xiang, P Samarati, J Hu, W Zhou & A-R Sadeghi (eds), 2010 Fourth International Conference on Network and System Security: NSS 2010. IEEE, Piscataway, N.J., USA, pp. 579-582, Fourth International Conference on Network and System Security (NSS 2010), Melbourne, Australia, 1/09/10. https://doi.org/10.1109/NSS.2010.19

Face gender recognition based on 2D principal component analysis and support vector machine. / Tran, Dat; Huang, Xu; Chetty, Girija.

2010 Fourth International Conference on Network and System Security: NSS 2010. ed. / Yang Xiang; Pierangela Samarati; Jiankun Hu; Wanlei Zhou; Ahmad-Reza Sadeghi. Piscataway, N.J., USA : IEEE, 2010. p. 579-582.

Research output: A Conference proceeding or a Chapter in BookConference contribution

TY - GEN

T1 - Face gender recognition based on 2D principal component analysis and support vector machine

AU - Tran, Dat

AU - Huang, Xu

AU - Chetty, Girija

PY - 2010

Y1 - 2010

N2 - This paper presents a novel method for solving face gender recognition problem. This method employs 2D Principal Component Analysis, one of the prominent methods for extracting feature vectors, and Support Vector Machine, the most powerful discriminative method for classification. Experiments for the proposed approach have been conducted on FERET data set and the results show that the proposed method could improve the classification rates.

AB - This paper presents a novel method for solving face gender recognition problem. This method employs 2D Principal Component Analysis, one of the prominent methods for extracting feature vectors, and Support Vector Machine, the most powerful discriminative method for classification. Experiments for the proposed approach have been conducted on FERET data set and the results show that the proposed method could improve the classification rates.

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DO - 10.1109/NSS.2010.19

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A2 - Xiang, Yang

A2 - Samarati, Pierangela

A2 - Hu, Jiankun

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A2 - Sadeghi, Ahmad-Reza

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Tran D, Huang X, Chetty G. Face gender recognition based on 2D principal component analysis and support vector machine. In Xiang Y, Samarati P, Hu J, Zhou W, Sadeghi A-R, editors, 2010 Fourth International Conference on Network and System Security: NSS 2010. Piscataway, N.J., USA: IEEE. 2010. p. 579-582 https://doi.org/10.1109/NSS.2010.19