Face Gender Recognition Based on 2D Principal Component Analysis and Support Vector Machine

Author

Bui, Len ; Tran, Dat ; Huang, Xu ; Chetty, Girija

Author_Institution

Fac. of Inf. Sci. & Eng., Univ. of Canberra, Canberra, ACT, Australia

fYear

2010

fDate

1-3 Sept. 2010

Firstpage

579

Lastpage

582

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.

Keywords

face recognition; feature extraction; principal component analysis; support vector machines; 2D principal component analysis; FERET data set; discriminative method; face gender recognition; support vector machine; Classification algorithms; Face; Face recognition; Feature extraction; Kernel; Principal component analysis; Support vector machines; Face Gender Recognition; Principal Component Analysis; Support Vector Machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Network and System Security (NSS), 2010 4th International Conference on

Conference_Location

Melbourne, VIC

Print_ISBN

978-1-4244-8484-3

Electronic_ISBN

978-0-7695-4159-4

Type

conf

DOI

10.1109/NSS.2010.19

Filename

5635939

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3089330