A floor sensor system for gait recognition
A floor sensor system for gait recognition
This paper describes the development of a prototype floor sensor as a gait recognition system. This could eventually find deployment as a standalone system (eg. a burglar alarm system) or as part of a multimodal biometric system. The new sensor consists of 1536 individual sensors arranged in a 3 m by 0.5 m rectangular strip with an individual sensor area of 3 cm2. The sensor floor operates at a sample rate of 22 Hz. The sensor itself uses a simple design inspired by computer keyboards and is made from low cost, off the shelf materials. Application of the sensor floor to a small database of 15 individuals was performed. Three features were extracted : stride length, stride cadence, and time on toe to time on heel ratio. Two of these measures have been used in video based gait recognition while the third is new to this analysis. These features proved sufficient to achieve an 80 % recognition rate.
Middleton, Lee
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Buss, Alex A.
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Bazin, Alex I.
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Nixon, Mark S.
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2005
Middleton, Lee
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Buss, Alex A.
91bfe4d4-ed54-44ee-807c-210939117d1a
Bazin, Alex I.
feead1f3-0fc6-4a1e-b089-f62361614633
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Middleton, Lee, Buss, Alex A., Bazin, Alex I. and Nixon, Mark S.
(2005)
A floor sensor system for gait recognition.
Fourth IEEE Workshop on Automatic Identification Advanced Technologies, Buffalo, New York, United States.
16 - 17 Oct 2005.
Record type:
Conference or Workshop Item
(Poster)
Abstract
This paper describes the development of a prototype floor sensor as a gait recognition system. This could eventually find deployment as a standalone system (eg. a burglar alarm system) or as part of a multimodal biometric system. The new sensor consists of 1536 individual sensors arranged in a 3 m by 0.5 m rectangular strip with an individual sensor area of 3 cm2. The sensor floor operates at a sample rate of 22 Hz. The sensor itself uses a simple design inspired by computer keyboards and is made from low cost, off the shelf materials. Application of the sensor floor to a small database of 15 individuals was performed. Three features were extracted : stride length, stride cadence, and time on toe to time on heel ratio. Two of these measures have been used in video based gait recognition while the third is new to this analysis. These features proved sufficient to achieve an 80 % recognition rate.
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c_middleton_autoid_2005.pdf
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More information
Published date: 2005
Additional Information:
Event Dates: 17-18 October
Venue - Dates:
Fourth IEEE Workshop on Automatic Identification Advanced Technologies, Buffalo, New York, United States, 2005-10-16 - 2005-10-17
Organisations:
Electronics & Computer Science, IT Innovation, Southampton Wireless Group
Identifiers
Local EPrints ID: 261537
URI: http://eprints.soton.ac.uk/id/eprint/261537
PURE UUID: 3d063f14-6d3a-486e-b87c-7b7096d51d8d
Catalogue record
Date deposited: 12 Nov 2005
Last modified: 18 Feb 2021 16:34
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Contributors
Author:
Lee Middleton
Author:
Alex A. Buss
Author:
Alex I. Bazin
University divisions
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