Scalable Biometric Travel Token Without Barriers to Access

Scalable Biometric Travel Token Without Barriers to Access

Niosha Kayhani Steffen Reym

Cubic Innovation Centre, Farringdon, London, UK

Page: 
https://doi.org/10.2495/TDI-V2-N2-166-175
|
DOI: 
166-175
Received: 
N/A
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Revised: 
N/A
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Accepted: 
N/A
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Available online: 
1 February 2018
| Citation

OPEN ACCESS

Abstract: 

Congestion at ticket gatelines is a growing problem. According to travel projections in the UK, the number of journeys for rail passengers is likely to double over the next 30 years. This creates the need to improve passenger throughput while still maintaining revenue protection. The proposed solution is to create a ‘Gateless Gateline’: a concept in which a user can seamlessly authenticate the intent to travel in train stations using current ticketing media ranging from barcode and Bluetooth low energy to radiofrequency identification, as well as new and emerging ticketing media, specifically related to biometrics. This article focuses on utilizing three-dimensional (3D) face recognition based on photometric stereo using near-infrared (NIR) light to illuminate a face for a 3D construction and tracking for the purpose of associating the correct biometric identifier with the correct person in a high-throughput environment. Other biometric systems have also been investigated as part of this project, i.e. palm vein scanning based on passing NIR light through the palm. There are challenges when it comes to associating passengers with valid travel tokens in a system which is free flowing and does not have a modus operandi of a standard access gate where validation occurs one at a time, normally signalled by paddles opening and closing. The proposed solution to the above, alongside the known issues associated with scaling biometric solutions, is reported in this article.

Keywords: 

biometrics, BLE, contactless, face recognition, Gateless Gateline, object tracking, machine learning, palm vein scanning, RFID

  References

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[3] Grabner, H., Grabner, M. & Bischof, H., Real-time tracking via on-line boosting. British Machine Vision Conference, 1(5), p. 6, 2006. DOI: 10.5244/C.20.6.