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Probabilistic Fusion of Gait Features for Biometric Verification

Record type: Conference or Workshop Item (Other)

This paper examines the fusion of various gait metrics in a probabilistic framework. Using three gait modalities we describe a process for determining probabilistic match scores using intra and inter-class variance models together with Bayes rule. We then propose to fuse these modalities based on established fusion rules with weights determined in a principled manner. Using a large publicly available database we show improvements through fusion, both in terms of verification accuracy and class separation; we also consider how the accuracy of each modality and the correlation between the modalities affects overall performance.

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Citation

Bazin, Alex I., Middleton, Lee and Nixon, Mark S. (2005) Probabilistic Fusion of Gait Features for Biometric Verification At Eighth International Conference of Information Fusion, 2005., United States. 25 - 29 Jul 2005.

More information

Published date: 2005
Additional Information: Event Dates: 25th-29th July 2005
Venue - Dates: Eighth International Conference of Information Fusion, 2005., United States, 2005-07-25 - 2005-07-29
Keywords: Fusion, Biometrics, Logistic function, Bayesian
Organisations: Electronics & Computer Science, IT Innovation, Southampton Wireless Group

Identifiers

Local EPrints ID: 261148
URI: http://eprints.soton.ac.uk/id/eprint/261148
PURE UUID: 9f848a09-e756-42de-b7a2-22dc163c6202

Catalogue record

Date deposited: 11 Aug 2005
Last modified: 18 Jul 2017 09:04

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