Gender classification via lips: static and dynamic features-Reference-Cited by-同舟云学术

Gender classification via lips: static and dynamic features

Published:2013-03 Issue:1 Volume:2 Page:28-34
ISSN:2047-4938
Container-title:IET Biometrics
language:en
Short-container-title:IET biom.

Author:

Stewart Darryl¹,Pass Adrian¹,Zhang Jianguo²

Affiliation:

1. Institute of Electronics, Communications and Information Technology (ECIT), Queens University Belfast Northern Ireland Science Park, Queen's Road, Queen's Island Belfast Northern Ireland BT3 9DT UK

2. School of Computing University of Dundee Dundee Scotland DD1 4HN UK

Publisher

Institution of Engineering and Technology (IET)

Subject

Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-bmt.2012.0021

Reference28 articles.

1. Evaluation of gender classification methods with automatically detected and aligned faces;Makinen E.;PAMI,2008

2. Stewart D. Wang H. Shen J. Miller P.: ‘Investigations into the robustness of audio‐visual gender classification to background noise and illumination effects’.Proc. 2009 Digital Image Computing: Techniques and Applications (DICTA’09) Washington DC USA 2009 pp.168–174

3. Learning gender with support faces

4. Shan C. Gong S. McOwan P.W.: ‘Learning gender from human gaits and faces’.AVSS’07: Proc. 2007 IEEE Conf. Advanced Video and Signal Based Surveillance Washington DC USA 2007 pp.505–510

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2. An automatic approach for classification and categorisation of lip morphological traits;PLOS ONE;2019-10-29

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4. Biometric Authentication for Gender Classification Techniques: A Review;Journal of The Institution of Engineers (India): Series B;2017-12-06

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