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dc.contributor.authorArandjelovic, O.
dc.contributor.authorPham, DucSon
dc.contributor.authorVenkatesh, S.
dc.contributor.editorEnrico Magli
dc.contributor.editorStefano Tubaro
dc.contributor.editorAnthony Vetro
dc.date.accessioned2017-01-30T12:26:01Z
dc.date.available2017-01-30T12:26:01Z
dc.date.created2016-09-22T12:29:04Z
dc.date.issued2015
dc.identifier.citationArandjelovic, O. and Pham, D. and Venkatesh, S. 2015. Viewpoint Distortion Compensation in Practical Surveillance Systems, in Enrico Magli, Stefano Tubaro, Anthony Vetro (ed), 2015 IEEE International Conference on Multimedia & Expo (ICME) , Jun 29 2015. Torino, Italy: IEEE.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/21572
dc.description.abstract

Our aim is to estimate the perspective-effected geometric distortion of a scene from a video feed. In contrast to all previous work we wish to achieve this using from low-level, spatio-temporally local motion features used in commercial semi-automatic surveillance systems. We: (i) describe a dense algorithm which uses motion features to estimate the perspective distortion at each image locus and then polls all such local estimates to arrive at the globally best estimate, (ii) present an alternative coarse algorithm which subdivides the image frame into blocks, and uses motion features to derive block-specific motion characteristics and constrain the relationships between these characteristics, with the perspective estimate emerging as a result of a global optimization scheme, and (iii) report the results of an evaluation using nine large sets acquired using existing close-circuit television (CCTV) cameras. Our findings demonstrate that both of the proposed methods are successful, their accuracy matching that of human labelling using complete visual data.

dc.publisherIEEE
dc.relation.urihttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7160935
dc.subjectnormalization
dc.subjectSurveillance
dc.subjectnovelty
dc.titleViewpoint Distortion Compensation in Practical Surveillance Systems
dc.typeConference Paper
dcterms.source.titleProceedings of the 2015 IEEE International Conference on Multimedia & Expo (ICME)
dcterms.source.seriesProceedings of the 2015 IEEE International Conference on Multimedia & Expo (ICME)
dcterms.source.isbn9781479970827
dcterms.source.conference2015 IEEE International Conference on Multimedia & Expo (ICME)
dcterms.source.conference-start-dateJun 29 2015
dcterms.source.conferencelocationTorino, Italy
dcterms.source.placeUSA
curtin.departmentDepartment of Computing
curtin.accessStatusFulltext not available


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