Content based video copy detection using motion vectors

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buir.advisorÇetin, A. Enis
dc.contributor.authorTaşdemir, Kasım
dc.date.accessioned2016-01-08T18:11:25Z
dc.date.available2016-01-08T18:11:25Z
dc.date.issued2009
dc.descriptionAnkara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Science of Bilkent University, 2009.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2009.en_US
dc.descriptionIncludes bibliographical references leaves 57-61.en_US
dc.description.abstractIn this thesis, we propose a motion vector based Video Content Based Copy Detection (VCBCD) method. Detecting the videos violating the copyright of the owner comes into question by growing broadcasting of digital video on different media. Unlike watermarking methods in VCBCD methods, the video itself is considered as a signature of the video and representative feature parameters are extracted from a given video and compared with the feature parameters of a test video. Motion vectors of image frames are one of the signatures of a given video. We first investigate how well the motion vectors describe the video. We use Mean value of Magnitudes of Motion Vectors (MMMV) and Mean value of Phases of Motion Vectors (MPMV) of macro blocks, which are the main building blocks of MPEG-type video coding methods. We show that MMMV and MPMV plots may not represent videos uniquely with little motion content because the average of motion vectors in a given frame approaches zero. To overcome this problem we calculate the MMMV and MPMV graphs in a lower frame rate than the actual frame rate of the video. In this way, the motion vectors may become larger and as a result robust signature plots are obtained. Another approach is to use the Histogram of Motion Vectors (HOMV) that includes both MMMV and MPMV information. We test and compare MMMV, MPMV and HOMV methods using test videos including copies and the original movies.en_US
dc.description.provenanceMade available in DSpace on 2016-01-08T18:11:25Z (GMT). No. of bitstreams: 1 0003922.pdf: 1113645 bytes, checksum: cb93e0fe552dd498e025fc29f14ffaa7 (MD5)en
dc.description.statementofresponsibilityTaşdemir, Kasımen_US
dc.format.extentxii, 61 leavesen_US
dc.identifier.urihttp://hdl.handle.net/11693/14950
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectContent Based Copy Detectionen_US
dc.subjectVideo Copy Detectionen_US
dc.subjectSequence Matchingen_US
dc.subjectMotion Vectorsen_US
dc.subjectSimilar Video Detectionen_US
dc.subject.lccQA76.575 .T37 2009en_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.titleContent based video copy detection using motion vectorsen_US
dc.typeThesisen_US
thesis.degree.disciplineElectrical and Electronic Engineering
thesis.degree.grantorBilkent University
thesis.degree.levelMaster's
thesis.degree.nameMS (Master of Science)

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