An Experimental Study on Automatic Face Gender Classification

Author

Yang, Zhiguang ; Li, Ming ; Ai, Haizhou

Author_Institution

Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing

Volume

3

fYear

0

fDate

0-0 0

Firstpage

1099

Lastpage

1102

Abstract

This paper presents an experimental study on automatic face gender classification by building a system that mainly consists of four parts, face detection, face alignment, texture normalization and gender classification. Comparative study on the effects of different texture normalization methods including two kinds of affine mapping and one Delaunay triangulation based warping as preprocesses for gender classification by SVM, LDA and real Adaboost respectively is reported through experiments on very large sets of snapshot images

Keywords

face recognition; image classification; image texture; mesh generation; Delaunay triangulation based warping; affine mapping; automatic face gender classification; face alignment; face detection; image texture normalization method; linear discriminant analysis; real Adaboost; support vector machine; Artificial intelligence; Computer science; Computer security; Electronic mail; Face detection; Face recognition; Nose; Shape; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2006. ICPR 2006. 18th International Conference on

Conference_Location

Hong Kong

ISSN

1051-4651

Print_ISBN

0-7695-2521-0

Type

conf

DOI

10.1109/ICPR.2006.247

Filename

1699717