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dc.contributor.authorKOKARAM, ANIL CHRISTOPHER
dc.contributor.editorTouradj Ebrahimi, Thomas Sikoraen
dc.date.accessioned2010-02-05T16:55:42Z
dc.date.available2010-02-05T16:55:42Z
dc.date.created8-11 julyen
dc.date.issued2003
dc.date.submitted2003en
dc.identifier.citationR. Dahyot, N. Rea and A. C. Kokaram `Sport Video Shot Segmentation and Classification? in proceedings SPIE Visual Communications and Image Processing 2003, University of Italian Switzerland (USI), Lugano, Switzerland, 8-11 july, eds Touradj Ebrahimi, Thomas Sikora, 5150, 2003, pp 404-413en
dc.identifier.otherY
dc.identifier.urihttp://hdl.handle.net/2262/37046
dc.descriptionPUBLISHEDen
dc.description.abstractThis paper considers the statistics of local appearance based measures that are suitable for the visual parsing of sport events. The moments of the colour information are computed, and the shape content in the frames is characterised by the moments of local shape measures. Their generation process is very low cost. The temporal evolution of the features then is modelled with a Hidden Markov Model. The HMM is used to generate higher level information by classifying the shots as close ups, court views, crowd shots and so on. The paper illustrates how those simple features, coupled with the HMM, can be used for parsing snooker and tennis footages.en
dc.format.extent404en
dc.format.extent413en
dc.format.extent5376752 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherSPIEen
dc.relation.ispartofseries5150en
dc.rightsYen
dc.subjectStatistical Momentsen
dc.subjectHidden Markov Modelen
dc.subjectshot classificationen
dc.titleSport Video Shot Segmentation and Classificationen
dc.typeConference Paperen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/akokaram
dc.identifier.rssinternalid27086
dc.identifier.rssurihttp://dx.doi.org/10.1117/12.503127


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