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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorPoppe, R.W.
dc.contributor.advisorDignum, F.P.M.
dc.contributor.authorDis, J. van
dc.date.accessioned2016-03-17T18:00:49Z
dc.date.available2016-03-17T18:00:49Z
dc.date.issued2016
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/22036
dc.description.abstractFinding the trajectory of sports persons in videos can be done in various ways. We address this problem for rugby 7s under difficult conditions, such as occlusion, a small camera angle with respect to the horizon, zooming, and supporters standing nearly in the field. A methodology is presented that processes videos of rugby 7s games during which simultaneously the camera parameters are derived - stating its location, orientation and internal settings such as focal length, and the position of the rugby players within the image plane are detected, to tracks their movements with respect to the ground plane. We propose a new method to determine the camera parameters effectively, making use of the recurring nature of the camera state, by only using a limited set of reference frames, called baseframes. Tracking is performed in the ground plane, using a tracking-by-detection approach with a Kalman filter to dynamically model the tracklets. An evaluation of our methodology shows the potential of our methodology. However, it is recommend to improve of the conditions under which tracking is performed.
dc.description.sponsorshipUtrecht University
dc.format.extent4654047
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.titleExtracting ground plane location data of rugby 7s players, from a zooming and rotating camera
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordscomputer vision, ground plane multi target tracking, camera modelling, camera pose estimation, Kalman filter, deformable parts model, object-detection
dc.subject.courseuuTechnical Artificial Intelligence


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