000185107 001__ 185107
000185107 005__ 20190604054651.0
000185107 0247_ $$2doi$$a10.1016/j.cviu.2013.11.010
000185107 022__ $$a1077-3142
000185107 02470 $$2ISI$$a000330752700007
000185107 037__ $$aARTICLE
000185107 245__ $$aTake your Eyes off the Ball: Improving Ball-Tracking by Focusing on Team Play
000185107 269__ $$a2014
000185107 260__ $$bElsevier$$c2014$$aSan Diego
000185107 300__ $$a14
000185107 336__ $$aJournal Articles
000185107 520__ $$aAccurate video-based ball tracking in team sports is important for automated game analysis, and has proven very difficult because the ball is often occluded by the players. In this paper, we propose a novel approach to addressing this issue by formulating the tracking in terms of deciding which player, if any, is in possession of the ball at any given time. This is very different from standard approaches that first attempt to track the ball and only then to assign possession. We will show that our method substantially increases performance when applied to long basketball and soccer sequences.
000185107 6531_ $$atracking
000185107 6531_ $$avideo analysis and event recognition
000185107 6531_ $$aocclusion reasoning
000185107 6531_ $$abehavior analysis
000185107 6531_ $$asports video
000185107 6531_ $$atracking the invisible
000185107 700__ $$0245095$$g199318$$aWang, Xinchao
000185107 700__ $$0245497$$g213153$$aAblavsky, Vitaly Henry
000185107 700__ $$0(EPFLAUTH)193130$$g193130$$aBen Shitrit, Horesh
000185107 700__ $$0240252$$g112366$$aFua, Pascal
000185107 773__ $$j119$$tComputer Vision and Image Understanding$$q102-115
000185107 8564_ $$uhttps://infoscience.epfl.ch/record/185107/files/top_infosci_1.pdf$$zPostprint$$s4575999$$yPostprint
000185107 909C0 $$xU10659$$0252087$$pCVLAB
000185107 909CO $$qGLOBAL_SET$$pIC$$ooai:infoscience.tind.io:185107$$particle
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000185107 937__ $$aEPFL-ARTICLE-185107
000185107 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000185107 980__ $$aARTICLE