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On the Relationship of Human Walking and Running: Automatic Person Identification by Gait

On the Relationship of Human Walking and Running: Automatic Person Identification by Gait
On the Relationship of Human Walking and Running: Automatic Person Identification by Gait
The intimate relationship between human walking and running lies within the skeleto-muscular structure. This is expressed as a mapping that can transform computer vision derived gait signatures from running to walking and vice versa, for purposes of deployment in gait as a biometric or for animation in computer graphics. The computer vision technique can extract leg motion by temporal template matching with a model defined by forced coupled oscillators as the basis. The (biometric) signature is derived from Fourier analysis of the variation in the motion of the thigh and lower leg. These signatures can be used for recognition by running or by walking. In fact, the mapping between these gait modes clusters better than the original signatures (of which running is the more potent) and can be used for recognition purposes alone, or to buttress both of the signatures. Moreover, the two signatures can be made invariant to gait mode by using the new mapping.
287-290
Yam, ChewYean
79143266-5774-4a7f-be45-0f3ff669acca
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Carter, John N.
e05be2f9-991d-4476-bb50-ae91606389da
Yam, ChewYean
79143266-5774-4a7f-be45-0f3ff669acca
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Carter, John N.
e05be2f9-991d-4476-bb50-ae91606389da

Yam, ChewYean, Nixon, Mark S. and Carter, John N. (2002) On the Relationship of Human Walking and Running: Automatic Person Identification by Gait. International Conference on Pattern Recognition (ICPR 2002). pp. 287-290 .

Record type: Conference or Workshop Item (Poster)

Abstract

The intimate relationship between human walking and running lies within the skeleto-muscular structure. This is expressed as a mapping that can transform computer vision derived gait signatures from running to walking and vice versa, for purposes of deployment in gait as a biometric or for animation in computer graphics. The computer vision technique can extract leg motion by temporal template matching with a model defined by forced coupled oscillators as the basis. The (biometric) signature is derived from Fourier analysis of the variation in the motion of the thigh and lower leg. These signatures can be used for recognition by running or by walking. In fact, the mapping between these gait modes clusters better than the original signatures (of which running is the more potent) and can be used for recognition purposes alone, or to buttress both of the signatures. Moreover, the two signatures can be made invariant to gait mode by using the new mapping.

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More information

Published date: August 2002
Additional Information: Event Dates: Aug, 2002
Venue - Dates: International Conference on Pattern Recognition (ICPR 2002), 2002-08-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 256413
URI: http://eprints.soton.ac.uk/id/eprint/256413
PURE UUID: 82ecc6f6-456f-49a5-a38f-e54d6158f738
ORCID for Mark S. Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 20 Nov 2003
Last modified: 10 Dec 2019 01:59

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