A stochastic approach to tracking objects across multiple cameras

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dc.contributor.authorDick, A.
dc.contributor.authorBrooks, M.
dc.contributor.conferenceAustralian Joint Conference on Artificial Intelligence (17th : 2004 : Cairns, Qld.)
dc.contributor.editorWebb, G.
dc.contributor.editorYu, X.
dc.date.issued2004
dc.descriptionThe original publication is available at www.springerlink.com
dc.description.abstractThis paper is about tracking people in real-time as they move through the non-overlapping fields of view of multiple video cameras. The paper builds upon existing methods for tracking moving objects in a single camera. The key extension is the use of a stochastic transition matrix to describe peoples observed patterns of motion both within and between fields of view. The parameters of the model for a particular environment are learnt simply by observing a person moving about in that environment. No knowledge of the environment or the configuration of the cameras is required.
dc.description.statementofresponsibilityAnthony R. Dick and Michael J. Brooks
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2004 / Webb, G., Yu, X. (ed./s), vol.3339, pp.160-170
dc.identifier.doi10.1007/b104336
dc.identifier.isbn3540240594
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.orcidDick, A. [0000-0001-9049-7345]
dc.identifier.orcidBrooks, M. [0000-0001-9612-5884]
dc.identifier.urihttp://hdl.handle.net/2440/29539
dc.language.isoen
dc.publisherSpringer
dc.publisher.placeBerlin, Germany
dc.relation.ispartofseriesLecture notes in computer science ; 3339.
dc.source.urihttp://springerlink.metapress.com/content/94mte4wja70ewv4y/?p=4ca39ca063794f50bba124183b37bbfa&pi=0
dc.titleA stochastic approach to tracking objects across multiple cameras
dc.typeConference paper
pubs.publication-statusPublished

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