New Area Based Metrics for Automatic Gait Recognition
New Area Based Metrics for Automatic Gait Recognition
Gait is a new biometric aimed to recognise a subject by the manner in which they walk. Gait has several advantages over other biometrics, most notably that it is non-invasive and perceivable at a distance when other biometrics are obscured. We present a new area based metric, called gait masks, which provides statistical data intimately related to the gait of the subject and motivated by medical studies. This provides the first statistical approach that can expose the dynamics of the change in area of a subject. Early results show promising results with a recognition rate of 90% on a standard database. Further, there appear to be performance advantages with respect to handling of noise associated with this new approach, together with capability for extension and generalisation. Future research will capitalise on the advantages of this new approach, together with analysis on a larger database.
233-242
Foster, Jeff P.
c917988b-b903-4845-9e64-6412e7ac33ab
Nixon, Mark S.
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Prudel-Bennett, Adam
b107a151-1751-4d8b-b8db-2c395ac4e14e
2001
Foster, Jeff P.
c917988b-b903-4845-9e64-6412e7ac33ab
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Prudel-Bennett, Adam
b107a151-1751-4d8b-b8db-2c395ac4e14e
Foster, Jeff P., Nixon, Mark S. and Prudel-Bennett, Adam
(2001)
New Area Based Metrics for Automatic Gait Recognition.
British Machine Vision Conference.
.
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Conference or Workshop Item
(Paper)
Abstract
Gait is a new biometric aimed to recognise a subject by the manner in which they walk. Gait has several advantages over other biometrics, most notably that it is non-invasive and perceivable at a distance when other biometrics are obscured. We present a new area based metric, called gait masks, which provides statistical data intimately related to the gait of the subject and motivated by medical studies. This provides the first statistical approach that can expose the dynamics of the change in area of a subject. Early results show promising results with a recognition rate of 90% on a standard database. Further, there appear to be performance advantages with respect to handling of noise associated with this new approach, together with capability for extension and generalisation. Future research will capitalise on the advantages of this new approach, together with analysis on a larger database.
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foster_bmvc2001.pdf
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Published date: 2001
Additional Information:
Event Dates: 2001
Venue - Dates:
British Machine Vision Conference, 2001-01-01
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 258453
URI: http://eprints.soton.ac.uk/id/eprint/258453
PURE UUID: 2abd19f5-9ae3-499b-861b-f477ea30cef9
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Date deposited: 08 Dec 2003
Last modified: 15 Mar 2024 02:35
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Contributors
Author:
Jeff P. Foster
Author:
Adam Prudel-Bennett
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