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2D and 3D face analysis for ticketless rail travel

Smith, Lyndon; Zhang, Wenhao; Smith, Melvyn L.

Authors

Lyndon Smith Lyndon.Smith@uwe.ac.uk
Professor in Computer Simulation and Machine

Dr Wenhao Zhang Wenhao.Zhang@uwe.ac.uk
Associate Professor of Computer Vision and Machine Learning

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Melvyn Smith Melvyn.Smith@uwe.ac.uk
Research Centre Director Vision Lab/Prof



Abstract

Research is reported into the design, implementation and functionalities of a vision system that employs the human face as a biometric for enabling ticketless rail travel. The system has been developed to optimise performance in the relatively unstructured railway station scenario. In addition to establishing the working vision
system, major outputs of the work have included demonstration that 3D face recovery prevents ‘spoofing’ by use of photographs; and also the finding that incorporation of 3D data into facial modelling has enabled a 6% improvement in face classification. Our conclusion is that 3D data increase face recognition reliability significantly and will be the enabling factor for ensuring revenue protection when employing vision systems for implementation of ticketless rail travel.

Citation

Smith, L., Zhang, W., & Smith, M. L. (2018). 2D and 3D face analysis for ticketless rail travel. In Proceedings of the 2018 International Conference on Image Processing, Computer Vision, & Pattern Recognition. , (16-22)

Conference Name International Conference on Image Processing, Computer Vision, & Pattern Recognition
Conference Location Vegas USA
Start Date Jul 30, 2018
End Date Aug 2, 2018
Acceptance Date May 1, 2018
Publication Date Jul 30, 2018
Deposit Date Mar 20, 2020
Pages 16-22
Book Title Proceedings of the 2018 International Conference on Image Processing, Computer Vision, & Pattern Recognition
ISBN 1-60132-485-5
Keywords 2D 3D face analysis biometric
Public URL https://uwe-repository.worktribe.com/output/5695886
Publisher URL https://csce.ucmss.com/cr/books/2018/ConferenceReport?ConferenceKey=IPC