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dc.contributor.authorDuong, Thi
dc.contributor.authorPhung, Dinh
dc.contributor.authorBui, H.H.
dc.contributor.authorVenkatesh, Svetha
dc.contributor.editorY.Y. Tang, S.P.Wang, G. Lorette, D.S. Young, H. Yang
dc.date.accessioned2017-01-30T15:30:28Z
dc.date.available2017-01-30T15:30:28Z
dc.date.created2014-10-28T02:23:12Z
dc.date.issued2006
dc.identifier.citationDuong, T. and Phung, D. and Bui, H.H. and Venkatesh, S. 2006. Human Behavior Recognition with Generic Exponential Family Duration Modeling in the Hidden Semi-Markov Model, in Tang, Y.Y. et al(ed), Proceedings of the 18th International Conference on Pattern Recognition, Aug 20-24 2006, pp. 202-207. Hong Kong: IEEE.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/46984
dc.identifier.doi10.1109/ICPR.2006.635
dc.description.abstract

The ability to learn and recognize human activities of daily living (ADLs) is important in building pervasive and smart environments. In this paper, we tackle this problem using the hidden semi-Markov model. We discuss the state-of-the-art duration modeling choices and then address a large class of exponential family distributions to model state durations. Inference and learning are efficiently addressed by providing a graphical representation for the model in terms of a dynamic Bayesian network (DBN). We investigate both discrete and continuous distributions from the exponential family (Poisson and inverse Gaussian respectively) for the problem of learning and recognizing ADLs. A full comparison between the exponential family duration models and other existing models including the traditional multinomial and the new Coxian are also presented. Our work thus completes a thorough investigation into the aspect of duration modeling and its application to human activities recognition in a real-world smart home surveillance scenario.

dc.publisherIEEE Coputer Society Conference Publishing Services
dc.titleHuman Behavior Recognition with Generic Exponential Family Duration Modeling in the Hidden Semi-Markov Model
dc.typeConference Paper
dcterms.source.startPage202
dcterms.source.endPage207
dcterms.source.titleProceedings of the 18th International Conference on Pattern Recognition Vol 3
dcterms.source.seriesProceedings of the 18th International Conference on Pattern Recognition Vol 3
dcterms.source.isbn0769525210
dcterms.source.conferenceInternational Conference on Pattern Recognition 2006
dcterms.source.conference-start-dateAug 20 2006
dcterms.source.conferencelocationHong Kong
dcterms.source.placeLos Alamitos, USA
curtin.departmentDepartment of Computing
curtin.accessStatusFulltext not available


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