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dc.contributor.authorHoad, TC
dc.contributor.authorZobel, J
dc.date.available2014-05-21T23:58:02Z
dc.date.issued2006-01-01
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000237469000001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=d4d813f4571fa7d6246bdc0dfeca3a1c
dc.identifier.citationHoad, T. C. & Zobel, J. (2006). Detection of video sequences using compact signatures. ACM TRANSACTIONS ON INFORMATION SYSTEMS, 24 (1), pp.1-50. https://doi.org/10.1145/1125857.1125858.
dc.identifier.issn1046-8188
dc.identifier.urihttp://hdl.handle.net/11343/29917
dc.description.abstract<jats:p>Digital representations are widely used for audiovisual content, enabling the creation of large online repositories of video, allowing access such as video on demand. However, the ease of copying and distribution of digital video makes piracy a growing concern for content owners. We investigate methods for identifying coderivative video content---that is, video clips that are derived from the same original source. By using dynamic programming to identify regions of similarity in video signatures, it is possible to efficiently and accurately identify coderivatives, even when these regions constitute only a small section of the clip being searched. We propose four new methods for producing compact video signatures, based on the way in which the video changes over time. The intuition is that such properties are likely to be preserved even when the video is badly degraded. We demonstrate that these signatures are insensitive to dramatic changes in video bitrate and resolution, two parameters that are often altered when reencoding. In the presence of mild degradations, our methods can accurately identify copies of clips that are as short as 5 s within a dataset 140 min long. These methods are much faster than previously proposed techniques; using a more compact signature, this query can be completed in a few milliseconds.</jats:p>
dc.languageEnglish
dc.publisherASSOC COMPUTING MACHINERY
dc.subjectInformation Systems
dc.titleDetection of video sequences using compact signatures
dc.typeJournal Article
dc.identifier.doi10.1145/1125857.1125858
melbourne.peerreviewPeer Reviewed
melbourne.affiliationThe University of Melbourne
melbourne.affiliation.departmentComputer Science and Software Engineering
melbourne.source.titleACM Transactions on Information Systems
melbourne.source.volume24
melbourne.source.issue1
melbourne.source.pages1-50
dc.research.codefor0806
dc.description.pagestart1
melbourne.publicationid122902
melbourne.elementsid309556
melbourne.contributor.authorZobel, Justin
dc.identifier.eissn1558-2868
melbourne.accessrightsThis item is currently not available from this repository


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