On Semantic Soft-Biometric Labels
On Semantic Soft-Biometric Labels
A new approach to soft biometrics aims to use human labelling as part of the process. This is consistent with analysis of surveillance video where people might be imaged at too low resolution or quality for conventional biometrics to be deployed. In this manner, people use anatomical descriptions of subjects to achieve recognition, rather than the usual measurements of personal characteristics used in biometrics. As such the labels need careful consideration in their construction, and should demonstrate correlation consistent with known human physiology. We describe our original process for generating these labels and analyse relationships between them. This gives insight into the perspicacity of using a human labelling system for biometric purposes.
3-15
Samangooei, Sina
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Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
2014
Samangooei, Sina
c380fb26-55d4-4b34-94e7-c92bbb26a40d
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Samangooei, Sina and Nixon, Mark S.
(2014)
On Semantic Soft-Biometric Labels.
Biomet 2014.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
A new approach to soft biometrics aims to use human labelling as part of the process. This is consistent with analysis of surveillance video where people might be imaged at too low resolution or quality for conventional biometrics to be deployed. In this manner, people use anatomical descriptions of subjects to achieve recognition, rather than the usual measurements of personal characteristics used in biometrics. As such the labels need careful consideration in their construction, and should demonstrate correlation consistent with known human physiology. We describe our original process for generating these labels and analyse relationships between them. This gives insight into the perspicacity of using a human labelling system for biometric purposes.
Text
Samangooei Biomet 2014.pdf
- Author's Original
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Published date: 2014
Venue - Dates:
Biomet 2014, 2014-01-01
Organisations:
Vision, Learning and Control
Identifiers
Local EPrints ID: 376713
URI: http://eprints.soton.ac.uk/id/eprint/376713
PURE UUID: 8fb67aa6-fc2b-41b7-bd58-4478d1a1fc17
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Date deposited: 01 May 2015 16:10
Last modified: 15 Mar 2024 02:35
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Author:
Sina Samangooei
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