Classification of Gender and Face Based on Gradient Faces

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

5 Citations (Scopus)

Abstract

This paper presents a new method for solving face gender identification and face classification problems. The proposed method uses gradient features for feature extraction and support vector machine for classification. Experiments for the proposed method have been conducted on two public data sets CalTech and AT&T. The results show that the proposed method could improve the classification rates
Original languageEnglish
Title of host publicationThe 3rd European Workshop on Visual Information Processing
EditorsAzeddine Beghdadi, Abdesselam Bouzerdoum, Giuseppe Boccignone, Mohamed-Chaker Larabi
Place of PublicationParis
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages269-272
Number of pages4
Volume1
ISBN (Print)9781457700729
DOIs
Publication statusPublished - 2011
EventEuropean Workshop on Visual Information Processing - Paris, Paris, France
Duration: 4 Jul 20116 Jul 2011

Conference

ConferenceEuropean Workshop on Visual Information Processing
CountryFrance
CityParis
Period4/07/116/07/11

Fingerprint

Support vector machines
Feature extraction
Experiments

Cite this

Tran, D., Huang, X., & Chetty, G. (2011). Classification of Gender and Face Based on Gradient Faces. In A. Beghdadi, A. Bouzerdoum, G. Boccignone, & M-C. Larabi (Eds.), The 3rd European Workshop on Visual Information Processing (Vol. 1, pp. 269-272). Paris: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EuVIP.2011.6045544
Tran, Dat ; Huang, Xu ; Chetty, Girija. / Classification of Gender and Face Based on Gradient Faces. The 3rd European Workshop on Visual Information Processing. editor / Azeddine Beghdadi ; Abdesselam Bouzerdoum ; Giuseppe Boccignone ; Mohamed-Chaker Larabi. Vol. 1 Paris : IEEE, Institute of Electrical and Electronics Engineers, 2011. pp. 269-272
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title = "Classification of Gender and Face Based on Gradient Faces",
abstract = "This paper presents a new method for solving face gender identification and face classification problems. The proposed method uses gradient features for feature extraction and support vector machine for classification. Experiments for the proposed method have been conducted on two public data sets CalTech and AT&T. The results show that the proposed method could improve the classification rates",
keywords = "Face Recognition, Local Binary Pattern",
author = "Dat Tran and Xu Huang and Girija Chetty",
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Tran, D, Huang, X & Chetty, G 2011, Classification of Gender and Face Based on Gradient Faces. in A Beghdadi, A Bouzerdoum, G Boccignone & M-C Larabi (eds), The 3rd European Workshop on Visual Information Processing. vol. 1, IEEE, Institute of Electrical and Electronics Engineers, Paris, pp. 269-272, European Workshop on Visual Information Processing, Paris, France, 4/07/11. https://doi.org/10.1109/EuVIP.2011.6045544

Classification of Gender and Face Based on Gradient Faces. / Tran, Dat; Huang, Xu; Chetty, Girija.

The 3rd European Workshop on Visual Information Processing. ed. / Azeddine Beghdadi; Abdesselam Bouzerdoum; Giuseppe Boccignone; Mohamed-Chaker Larabi. Vol. 1 Paris : IEEE, Institute of Electrical and Electronics Engineers, 2011. p. 269-272.

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

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AB - This paper presents a new method for solving face gender identification and face classification problems. The proposed method uses gradient features for feature extraction and support vector machine for classification. Experiments for the proposed method have been conducted on two public data sets CalTech and AT&T. The results show that the proposed method could improve the classification rates

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KW - Local Binary Pattern

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Tran D, Huang X, Chetty G. Classification of Gender and Face Based on Gradient Faces. In Beghdadi A, Bouzerdoum A, Boccignone G, Larabi M-C, editors, The 3rd European Workshop on Visual Information Processing. Vol. 1. Paris: IEEE, Institute of Electrical and Electronics Engineers. 2011. p. 269-272 https://doi.org/10.1109/EuVIP.2011.6045544