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Gender recognition based on computer vision system


Authors

Li-Hong Juang ()*

School of Electrical Engineering and Automation, Xiamen University of Technology, No.600, Ligong Road, Jimei, 360124, P.R.China

 
Ming-Ni Wu

Department of Information Management, National Taichung University of Technology, Taichung, Taiwan

 
Shin-An Lin

Department of Information Management, National Taichung University of Technology, Taichung, Taiwan

 


Abstract

Detecting human gender from complex background, illumination variations and objects under computer vision system is very difficult but important for an adaptive information service. In this paper, a preliminary design and some experimental results of gender recognition will be presented from the walking movement that utilizes the gait-energy image (GEI) with denoised energy image (DEI) pre-processing as a machine learning support vector machine (SVM) classifier to train and extract its characteristics. The results show that the proposed method can adopt some characteristic values and the accuracy can reach up to 100% gender recognition rate under combining the horizontal added vertical feature and using a normal image size and test data when people are walking at a fixed angle. Meanwhile, it will be able to achieve over 80% rate within some allowed fault-tolerant angle range.


Keywords


Pages

Total Pages: 8
Pages: 249-256

DOI
10.1080/10798587.2016.1272777


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Published

Volume: 24
Issue: 2
Year: 2018

Cite this document


References

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JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present




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