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dc.contributor.authorDAWSON-HOWE, KENNETH MARK
dc.contributor.editorJesse Hoey, Stephen McKenna and Emanuele Truccoen
dc.date.accessioned2012-06-27T12:30:10Z
dc.date.available2012-06-27T12:30:10Z
dc.date.created29/8/2011 - 2/9/2011en
dc.date.issued2011
dc.date.submitted2011en
dc.identifier.citationDarren Caulfield and Kenneth Dawson-Howe, Track validation using gradient-based normalised cross-correlation, British Machine Vision Conference, Dundee, Scotland., 29/8/2011 - 2/9/2011, Jesse Hoey, Stephen McKenna and Emanuele Trucco, BMVA Press, 2011, 70.1 - 70.11en
dc.identifier.otherY
dc.identifier.urihttp://hdl.handle.net/2262/64040
dc.descriptionPUBLISHEDen
dc.description.abstractWe develop a gradient-based normalised cross-correlation tracker that is as robust as brute-force template matching while being signi?cantly more computationally ef?cient. The technique serves as the basis of our track validation algorithm: by tracking an object forwards in time, reinitialising at the end of the sequence and then tracking backwards in time, we can determine whether or not the object has been followed correctly ? the forwards and backwards trajectories will be very different for tracking failures. If such a failure occurs, we iteratively attempt to validate shorter portions of the video sequence until validation is achieved. The algorithm provides a means of determining whether or not an object was tracked successfully without the need for ground truth data.en
dc.format.extent70.1en
dc.format.extent70.11en
dc.language.isoenen
dc.publisherBMVA Pressen
dc.rightsYen
dc.subjectcross-correlationen
dc.subjectbrute-force template matchingen
dc.subjecttrack validationen
dc.subjectNCCen
dc.titleTrack validation using gradient-based normalised cross-correlationen
dc.title.alternativeBritish Machine Vision Conferenceen
dc.typeConference Paperen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/kdawson
dc.identifier.rssinternalid75795
dc.identifier.rssurihttp://www.bmva.org/bmvc/2011/proceedings/paper70/paper70.pdfen


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