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dc.contributor.authorLuhr, Sebastian
dc.contributor.authorVenkatesh, Svetha
dc.contributor.authorWest, Geoffrey
dc.contributor.authorBui, Hung H.
dc.contributor.editorChengqi Zhang
dc.contributor.editorHans W Guesgen
dc.contributor.editorWai K Yeap
dc.date.accessioned2017-01-30T11:09:41Z
dc.date.available2017-01-30T11:09:41Z
dc.date.created2010-11-17T07:05:02Z
dc.date.issued2004
dc.identifier.citationLuhr, Sebastian and Venkatesh, Svetha and West, Geoffrey and Bui, Hung H. 2004. Explicit state duration HMM for abnormality detection in sequences of human activity, in Chengqi Zhang, Hans W Guesgen, Wai K Yeap (ed), 8th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2004), Aug 9 2004, pp. 983-984.Auckland, New Zealand: Springer-Verlag
dc.identifier.urihttp://hdl.handle.net/20.500.11937/8946
dc.identifier.doi10.1007/978-3-540-28633-2_125
dc.description.abstract

Much of the current work in human behaviour modelling concentrates on activity recognition, recognising actions and events through pose, movement, and gesture analysis. Our work focuses on learning and detecting abnormality in higher level behavioural patterns. The hidden Markov model (HMM) is one approach for learning such behaviours given a vision tracker recording observations about a persons activity. Duration of human activity is an important consideration if we are to accurately model a persons behavioural patterns. We show how the implicit state duration in the HMM can create a situation in which highly abnormal deviation as either less than or more than the usually observed activity duration can fail to be detected and how the explicit state duration HMM (ESD-HMM) helps alleviate the problem.

dc.publisherSpringer-Verlag
dc.titleExplicit state duration HMM for abnormality detection in sequences of human activity
dc.typeConference Paper
dcterms.source.volumeAugust
dcterms.source.startPage983
dcterms.source.endPage984
dcterms.source.title8th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2004)
dcterms.source.series8th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2004)
dcterms.source.isbn3540228179
dcterms.source.conference8th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2004)
dcterms.source.conference-start-dateAug 9 2004
dcterms.source.conferencelocationAuckland, New Zealand
dcterms.source.placeBerlin, Heidelberg, Germany
curtin.accessStatusFulltext not available
curtin.facultySchool of Science and Computing
curtin.facultyDepartment of Computing
curtin.facultyFaculty of Science and Engineering


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