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dc.contributor.advisorŞahin, Pınar Duygulu
dc.contributor.authorCan, Tolga
dc.date.accessioned2016-01-08T18:02:42Z
dc.date.available2016-01-08T18:02:42Z
dc.date.issued2007
dc.identifier.urihttp://hdl.handle.net/11693/14589
dc.descriptionAnkara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2007.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2007.en_US
dc.descriptionIncludes bibliographical references leaves 87-92.en_US
dc.description.abstractIn this thesis, we propose a new method to search different instances of a video sequence inside a long video. The proposed method is robust to view point and illumination changes which may occur since the sequences are captured in different times with different cameras, and to the differences in the order and the number of frames in the sequences which may occur due to editing. The algorithm does not require any query to be given for searching, and finds all repeating video sequences inside a long video in a fully automatic way. First, the frames in a video are ranked according to their similarity on the distribution of salient points and colour values. Then, a tree based approach is used to seek for the repetitions of a video sequence if there is any. These repeating sequences are pruned for more accurate results in the last step. Results are provided on two full length feature movies, Run Lola Run and Groundhog Day, on commercials of TRECVID 2004 news video corpus and on dataset created for CIVR Copy Detection Showcase 2007. In these experiments, we obtain %93 precision values for CIVR2007 Copy Detection Showcase dataset and exceed %80 precision values for other sets.en_US
dc.description.statementofresponsibilityCan, Tolgaen_US
dc.format.extentxii, 92 leaves, illustrationsen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCopy detectionen_US
dc.subjectMedia trackingen_US
dc.subjectStory trackingen_US
dc.subject.lccQA76.575 .C36 2007en_US
dc.subject.lcshMultimedia systems.en_US
dc.subject.lcshDigital video.en_US
dc.subject.lcshVideo recordings.en_US
dc.subject.lcshDigital computer.en_US
dc.titleDetection and tracking of repeated sequences in videosen_US
dc.typeThesisen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US
dc.identifier.itemidBILKUTUPB103943


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