Robust Background estimator using IMM

Deshpande, S; Challa, S

Robust Background estimator using IMM

Deshpande, S Challa, S

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2007 Information, Decision and Control, 2007, pp. 130 - 135
Issue Date:: 2007-01

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Field	Value	Language
dc.contributor.author	Deshpande, S	en_US
dc.contributor.author	Challa, S	en_US
dc.contributor.editor	David Kershaw	en_US
dc.date	2007-02-12	en_US
dc.date.issued	2007-01	en_US
dc.identifier.citation	2007 Information, Decision and Control, 2007, pp. 130 - 135	en_US
dc.identifier.isbn	1-4244-0902-0	en_US
dc.identifier.uri	http://hdl.handle.net/10453/17413
dc.description.abstract	Intelligent video surveillance applications are frequently used nowadays. For such applications, background estimation becomes an important building block. In indoor environments, the switching of light takes place often. The previous approaches do not adapt quite well to the light switch. They take a long time to react to this problem. We attempt to tackle this problem by modeling it as a multiple model estimation problem. The well known IMM (Interacting Multiple Model) estimator which has been successful in tracking maneuvering targets is used to tackle the light switch problem. The results show that it can easily detect the light switch with less error.	en_US
dc.publisher	IEEE	en_US
dc.relation.ispartof	2007 Information, Decision and Control	en_US
dc.relation.ispartof	Information, Decision and Control	en_US
dc.relation.isbasedon	10.1109/IDC.2007.374538	en_US
dc.rights	© 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.title	Robust Background estimator using IMM	en_US
dc.type	Conference Proceeding
utslib.location	USA	en_US
utslib.location.activity	Adelaide, Australia	en_US
utslib.for	1005 Communications Technologies	en_US
dc.location.activity	Adelaide, Australia	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	closed_access
pubs.consider-herdc	false	en_US
pubs.place-of-publication	USA	en_US
pubs.start-date	2007-02-12	en_US

Abstract:

Intelligent video surveillance applications are frequently used nowadays. For such applications, background estimation becomes an important building block. In indoor environments, the switching of light takes place often. The previous approaches do not adapt quite well to the light switch. They take a long time to react to this problem. We attempt to tackle this problem by modeling it as a multiple model estimation problem. The well known IMM (Interacting Multiple Model) estimator which has been successful in tracking maneuvering targets is used to tackle the light switch problem. The results show that it can easily detect the light switch with less error.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/17413