000182800 001__ 182800
000182800 005__ 20190316235537.0
000182800 022__ $$a0932-8092
000182800 037__ $$aARTICLE
000182800 245__ $$aTracking Multiple Players using a Single Camera
000182800 269__ $$a2013
000182800 260__ $$bSpringer Verlag$$c2013
000182800 336__ $$aJournal Articles
000182800 520__ $$aIt has been shown that multi-people tracking could be successfullly formulated as a Linear Program to process the output of multiple fixed and synchronized cameras with overlapping fields of view. In this paper, we extend this approach to the more challenging single-camera case and show that it yields excellent performance, even when the camera moves. We validate our approach on a number of basketball matches and argue that using a properly retrained people detector is key to producing the probabilities of presence that are used as input to the Linear Program.
000182800 6531_ $$aMonocular Tracking
000182800 700__ $$0242722$$g193130$$aBen Shitrit, Horesh
000182800 700__ $$0244458$$g202799$$aRaca, Mirko
000182800 700__ $$0240254$$g146262$$aFleuret, François
000182800 700__ $$0240252$$g112366$$aFua, Pascal
000182800 773__ $$tMachine Vision and Applications
000182800 8564_ $$uhttps://infoscience.epfl.ch/record/182800/files/top.pdf$$zn/a$$s6345540$$yn/a
000182800 909C0 $$xU10659$$0252087$$pCVLAB
000182800 909CO $$qGLOBAL_SET$$pIC$$ooai:infoscience.tind.io:182800$$particle
000182800 917Z8 $$x112366
000182800 917Z8 $$x112366
000182800 917Z8 $$x112366
000182800 937__ $$aEPFL-ARTICLE-182800
000182800 973__ $$rREVIEWED$$sSUBMITTED$$aEPFL
000182800 980__ $$aARTICLE