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Proceedings Paper

Gender recognition based on face geometric features
Author(s): Jie Xiao; Zhaoli Guo; Chao Cai
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Paper Abstract

Automatic gender recognition based on face images plays an important role in computer vision and machine vision. In this paper, a novel and simple gender recognition method based on face geometric features is proposed. The method is divided in three steps. Firstly, Pre-processing step provides standard face images for feature extraction. Secondly, Active Shape Model (ASM) is used to extract geometric features in frontal face images. Thirdly, Adaboost classifier is chosen to separate the two classes (male and female). We tested it on 2570 pictures (1420 males and 1150 females) downloaded from the internet, and encouraging results were acquired. The comparison of the proposed geometric feature based method and the full facial image based method demonstrats its superiority.

Paper Details

Date Published: 27 October 2013
PDF: 6 pages
Proc. SPIE 8919, MIPPR 2013: Pattern Recognition and Computer Vision, 89190R (27 October 2013); doi: 10.1117/12.2031321
Show Author Affiliations
Jie Xiao, Huazhong Univ. of Science and Technology (China)
Wuchang Univ. of Technology (China)
Zhaoli Guo, Huazhong Univ. of Science and Technology (China)
Chao Cai, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 8919:
MIPPR 2013: Pattern Recognition and Computer Vision
Zhiguo Cao, Editor(s)

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