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dc.contributor.authorHoseinnezhad, R.
dc.contributor.authorVo, Ba-Ngu
dc.contributor.authorVo, Ba Tuong
dc.date.accessioned2017-01-30T10:34:16Z
dc.date.available2017-01-30T10:34:16Z
dc.date.created2014-03-12T20:01:04Z
dc.date.issued2013
dc.identifier.citationHoseinnezhad, Reza and Vo, Ba-Ngu and Vo, Ba-Tuong. 2013. Visual Tracking in Background Subtracted Image Sequences via Multi-Bernoulli Filtering. IEEE Transactions on Signal Processing. 61 (2): pp. 392-397.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/3820
dc.identifier.doi10.1109/TSP.2012.2222389
dc.description.abstract

This correspondence presents a novel method for simultaneous tracking of multiple non-stationary targets in video. Our method operates directly on the video data and does not require any detection. We propose a multi-target likelihood function for the background-subtracted grey-scale image data, which admits multi-target conjugate priors. This allows the multi-target posterior to be efficiently propagated forward using the multi-Bernoulli filter. Our method does not need any training pattern or target templates and makes no prior assumptions about object types or object appearance. Case studies from the CAVIAR dataset show that our method can automatically track multiple targets and quickly finds targets entering or leaving the scene.

dc.publisherInstitute of Electrical and Electronics Engineers
dc.titleVisual Tracking in Background Subtracted Image Sequences via Multi-Bernoulli Filtering
dc.typeJournal Article
dcterms.source.volume61
dcterms.source.number2
dcterms.source.startPage392
dcterms.source.endPage397
dcterms.source.issn1053-587X
dcterms.source.titleIEEE Transactions on Signal Processing
curtin.department
curtin.accessStatusFulltext not available


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