The University of Southampton
University of Southampton Institutional Repository

Model-Based Gait Enrolment in Real-World Imagery

Model-Based Gait Enrolment in Real-World Imagery
Model-Based Gait Enrolment in Real-World Imagery
We present a model-based approach to gait extraction that is capable of reliable operation on real-world imagery. Hierarchies of shape and motion are employed to yield relatively modest computational demands, avoiding the high-dimensional search spaces associated with complex models. Anatomical data is used to generate shape models consistent with normal human body proportions. Mean gait data is used to create prototype gait motion models, which are adapted to fit individual subjects. Accuracy is evaluated on subjects filmed from a fronto-parallel view in controlled laboratory conditions, for which some gait parameters are known. We further show that comparable performance is attained in outdoor conditions. As such, we describe a new approach to enrolment for gait recognition technologies, allowing reliable subject gait extraction in real-world imagery.
gait, walking, model-based
189-195
Wagg, David K
a6df8725-c301-4516-8cfc-e63afacfb166
Nixon, Mark S
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Wagg, David K
a6df8725-c301-4516-8cfc-e63afacfb166
Nixon, Mark S
2b5b9804-5a81-462a-82e6-92ee5fa74e12

Wagg, David K and Nixon, Mark S (2003) Model-Based Gait Enrolment in Real-World Imagery. Workshop on Multimodal User Authentication, Santa Barbara, CA, United States. 11 - 12 Dec 2003. pp. 189-195 .

Record type: Conference or Workshop Item (Paper)

Abstract

We present a model-based approach to gait extraction that is capable of reliable operation on real-world imagery. Hierarchies of shape and motion are employed to yield relatively modest computational demands, avoiding the high-dimensional search spaces associated with complex models. Anatomical data is used to generate shape models consistent with normal human body proportions. Mean gait data is used to create prototype gait motion models, which are adapted to fit individual subjects. Accuracy is evaluated on subjects filmed from a fronto-parallel view in controlled laboratory conditions, for which some gait parameters are known. We further show that comparable performance is attained in outdoor conditions. As such, we describe a new approach to enrolment for gait recognition technologies, allowing reliable subject gait extraction in real-world imagery.

Text
mmua03_model-based_gait.pdf - Other
Download (561kB)

More information

Published date: December 2003
Additional Information: Event Dates: December 11-12 2003
Venue - Dates: Workshop on Multimodal User Authentication, Santa Barbara, CA, United States, 2003-12-11 - 2003-12-12
Keywords: gait, walking, model-based
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 258842
URI: http://eprints.soton.ac.uk/id/eprint/258842
PURE UUID: 9c424e19-8dfd-4e8c-b441-cbb635859226
ORCID for Mark S Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 23 May 2004
Last modified: 15 Mar 2024 02:35

Export record

Contributors

Author: David K Wagg
Author: Mark S Nixon ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×