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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

Wenhao Zhang Wenhao.Zhang@uwe.ac.uk
Senior Lecturer in Machine Vision

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.

Start Date Jul 30, 2018
Publication Date Jul 30, 2018
Pages 16-22
Book Title Proceedings of the 2018 International Conference on Image Processing, Computer Vision, & Pattern Recognition
ISBN 1-60132-485-5
APA6 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)
Keywords 2D 3D face analysis biometric
Publisher URL https://csce.ucmss.com/cr/books/2018/ConferenceReport?ConferenceKey=IPC
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