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

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4 Author(s)
Len Bui ; Fac. of Inf. Sci. & Eng., Univ. of Canberra, Canberra, ACT, Australia ; Dat Tran ; Xu Huang ; Girija Chetty

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.

Published in:

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

Date of Conference:

1-3 Sept. 2010