A smart environment for biometric capture
A smart environment for biometric capture
The development of large scale biometric systems require experiments to be performed on large amounts of data. Existing capture systems are designed for fixed experiments and are not easily scalable. In this scenario even the addition of extra data is difficult. We developed a prototype biometric tunnel for the capture of non-contact biometrics. It is self contained and autonomous. Such a configuration is ideal for building access or deployment in secure environments. The tunnel captures cropped images of the subject's face and performs a 3D reconstruction of the person's motion which is used to extract gait information. Interaction between the various parts of the system is performed via the use of an agent framework. The design of this system is a trade-off between parallel and serial processing due to various hardware bottlenecks. When tested on a small population the extracted features have been shown to be potent for recognition. We currently achieve a moderate throughput of approximate 15 subjects an hour and hope to improve this in the future as the prototype becomes more complete.
Middleton, Lee
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Wagg, David K.
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Bazin, Alex I.
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Carter, John N.
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Nixon, Mark S.
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2006
Middleton, Lee
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Wagg, David K.
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Bazin, Alex I.
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Carter, John N.
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Nixon, Mark S.
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Middleton, Lee, Wagg, David K., Bazin, Alex I., Carter, John N. and Nixon, Mark S.
(2006)
A smart environment for biometric capture.
IEEE Conference on Automation Science and Engineering, Shanghai, China.
Record type:
Conference or Workshop Item
(Paper)
Abstract
The development of large scale biometric systems require experiments to be performed on large amounts of data. Existing capture systems are designed for fixed experiments and are not easily scalable. In this scenario even the addition of extra data is difficult. We developed a prototype biometric tunnel for the capture of non-contact biometrics. It is self contained and autonomous. Such a configuration is ideal for building access or deployment in secure environments. The tunnel captures cropped images of the subject's face and performs a 3D reconstruction of the person's motion which is used to extract gait information. Interaction between the various parts of the system is performed via the use of an agent framework. The design of this system is a trade-off between parallel and serial processing due to various hardware bottlenecks. When tested on a small population the extracted features have been shown to be potent for recognition. We currently achieve a moderate throughput of approximate 15 subjects an hour and hope to improve this in the future as the prototype becomes more complete.
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c_middleton_case_2006.pdf
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Published date: 2006
Additional Information:
Event Dates: October
Venue - Dates:
IEEE Conference on Automation Science and Engineering, Shanghai, China, 2006-10-01
Organisations:
Electronics & Computer Science, IT Innovation, Southampton Wireless Group
Identifiers
Local EPrints ID: 262914
URI: http://eprints.soton.ac.uk/id/eprint/262914
PURE UUID: abb28ebb-ef2f-4718-96e2-6ed287550051
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Date deposited: 18 Aug 2006
Last modified: 15 Mar 2024 02:35
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Contributors
Author:
Lee Middleton
Author:
David K. Wagg
Author:
Alex I. Bazin
Author:
John N. Carter
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