Gender recognition based on face geometric features

Jie Xiao; Zhaoli Guo; Chao Cai

doi:10.1117/12.2031321

27 October 2013 Gender recognition based on face geometric features

Jie Xiao, Zhaoli Guo, Chao Cai

Proceedings Volume 8919, MIPPR 2013: Pattern Recognition and Computer Vision; 89190R (2013) https://doi.org/10.1117/12.2031321
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China

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.

Citation Download Citation

Jie Xiao, Zhaoli Guo, and Chao Cai "Gender recognition based on face geometric features", Proc. SPIE 8919, MIPPR 2013: Pattern Recognition and Computer Vision, 89190R (27 October 2013); https://doi.org/10.1117/12.2031321

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