DocumentCode
1704294
Title
The University of Southampton Multi-Biometric Tunnel and introducing a novel 3D gait dataset
Author
Seely, Richard D. ; Samangooei, Sina ; Lee, Minhung ; Carter, John N. ; Nixon, Mark S.
Author_Institution
Sch. of Electron. & Comput. Sci., Univ. of Southampton, Southampton
fYear
2008
Firstpage
1
Lastpage
6
Abstract
This paper presents the University of Southampton multi-biometric tunnel, a constrained environment that is designed with airports and other high throughput environments in mind. It is able to acquire a variety of non-contact biometrics in a non-intrusive manner. The system uses eight synchronised IEEE1394 cameras to capture gait and additional cameras to capture images from the face and one ear, as an individual walks through the tunnel. We demonstrate that it is possible to achieve a 99.6% correct classification rate and a 4.3% equal error rate without feature selection using the gait data collected from the system; comparing well with state-of-art approaches. The tunnel acquires data automatically as a subject walks through it and is designed for the collection of very large gait datasets.
Keywords
biometrics (access control); feature extraction; gesture recognition; image classification; 3D gait dataset; IEEE1394 cameras; University of Southampton; feature selection; multi-biometric tunnel; noncontact biometrics; Airports; Application software; Automatic control; Biometrics; Cameras; Computer vision; Data security; Lighting control; Medical diagnostic imaging; Throughput;
fLanguage
English
Publisher
ieee
Conference_Titel
Biometrics: Theory, Applications and Systems, 2008. BTAS 2008. 2nd IEEE International Conference on
Conference_Location
Arlington, VA
Print_ISBN
978-1-4244-2729-1
Electronic_ISBN
978-1-4244-2730-7
Type
conf
DOI
10.1109/BTAS.2008.4699353
Filename
4699353
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