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
December 2003
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.
.
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
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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
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Date deposited: 23 May 2004
Last modified: 15 Mar 2024 02:35
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Contributors
Author:
David K Wagg
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