An experimental comparison of gender classification methods

被引：129

作者：

Makinen, Erno ^{[1
]}

Raisamo, Roope ^{[1
]}

机构：

[1] Univ Tampere, Dept Comp Sci, Multimodal Interact Res Grp, Tampere Unit Comp Human Interact, FIN-33014 Tampere, Finland

来源：

PATTERN RECOGNITION LETTERS | 2008年 / 29卷 / 10期

关键词：

automatic face analysis; gender classification; face detection; face database; performance evaluation;

D O I：

10.1016/j.patrec.2008.03.016

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Successful face analysis requires robust methods. It has been hard to compare the methods due to different experimental setups. We carried out a comparison study for the state-of-the-art gender classification methods to find out their actual reliability. The main contributions are comprehensive and comparable classification results for the gender classification methods combined with automatic real-time face detection and, in addition, with manual face normalization. We also experimented by combining gender classifier outputs arithmetically. This lead to increased classification accuracies. Furthermore, we contribute guidelines to carry out classification experiments, knowledge on the strengths and weaknesses of the gender classification methods, and two new variants of the known methods. (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：1544 / 1556

页数：13

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