Abstract
We present a method for tracking people in monocular broadcast sports videos by coupling a particle filter with a vote-based confidence map of athletes, appearance features and optical flow for motion estimation. The confidence map provides a continuous estimate of possible target locations in each frame and outperforms tracking with discrete target detections. We demonstrate the tracker on sports videos, tracking fast and articulated movements of athletes such as divers and gymnasts and on non-sports videos, tracking pedestrians in a PETS2009 sequence.
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Yao, A., Uebersax, D., Gall, J., Van Gool, L. (2010). Tracking People in Broadcast Sports. In: Goesele, M., Roth, S., Kuijper, A., Schiele, B., Schindler, K. (eds) Pattern Recognition. DAGM 2010. Lecture Notes in Computer Science, vol 6376. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15986-2_16
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DOI: https://doi.org/10.1007/978-3-642-15986-2_16
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