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Fusing Complementary Operators to Enhance Foreground/Background Segmentation

Al-Mazeed, Ahmad H., Nixon, Mark S. and Gunn, Steve R., (2003) Fusing Complementary Operators to Enhance Foreground/Background Segmentation Harvey, Richard and Bagham, J. Andrew (eds.) At British Machine Vision Conference 2003. , pp. 501-510.

Record type: Conference or Workshop Item (Paper)

Abstract

Foreground/background segmentation is an active research area for moving object analysis. We combine two probabilistic approaches one of which estimates foreground/background probabilistic density and the other uses prior knowledge to decompose the colour space. The observed performance advantages are associated with the fusion of operators with completely different basis. Tests on outdoor and indoor sequences confirm the efficacy of this approach. The new algorithms can successfully identify and remove shadows and highlights with improved moving-object segmentation. A particular advantage of our evaluation is that it is the first approach that compares foreground/ background labelling with results obtained from labelling by broadcast techniques.

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More information

Published date: 2003
Additional Information: Event Dates: 2003
Venue - Dates: British Machine Vision Conference 2003, 2003-01-01
Keywords: Motion Segmentation, Mixture Models, Foregraound/ Background Labelling, Gait
Organisations: Electronic & Software Systems, Southampton Wireless Group

Identifiers

Local EPrints ID: 258445
URI: http://eprints.soton.ac.uk/id/eprint/258445
PURE UUID: 45e90b20-17d7-4613-b3a5-9b2672598268

Catalogue record

Date deposited: 20 Nov 2003
Last modified: 18 Jul 2017 09:32

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Contributors

Author: Ahmad H. Al-Mazeed
Author: Mark S. Nixon
Author: Steve R. Gunn
Editor: Richard Harvey
Editor: J. Andrew Bagham

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