What Players do with the Ball: A Physically Constrained Interaction Modeling
Tracking the ball is critical for video-based analysis of team sports. However, it is difficult, especially in lowresolution images, due to the small size of the ball, its speed that creates motion blur, and its often being occluded by players. We propose a generic and principled approach to modeling the interaction between the ball and the players while also imposing appropriate physical constraints on the ball’s trajectory. We show that our approach, formulated in terms of a Mixed Integer Program, is more robust and more accurate than several state-of-the-art approaches on real-life volleyball, basketball, and soccer sequences.
Results
We show our ball tracking results on volleyball, basketball and soccer sequences as follows.
Volley1 dataset
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Volley2 dataset
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Basket1 dataset
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Basket2 dataset
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APIDIS dataset
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ISSIA dataset
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Play the Basketball Roulette!
Try your luck at guessing where the ball is here and see if you can beat the algorithm!
References
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What Players do with the Ball: A Physically Constrained Interaction Modeling
2016. International Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, Jun 26 – Jul 1 2016. p. 972-981. DOI : 10.1109/CVPR.2016.111.Please note that the publication lists from Infoscience integrated into the EPFL website, lab or people pages are frozen following the launch of the new version of platform. The owners of these pages are invited to recreate their publication list from Infoscience. For any assistance, please consult the Infoscience help or contact support.