Ball Tracking in Team Sports

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

Volley2 dataset

Basket1 dataset

Basket2 dataset

APIDIS dataset

ISSIA dataset

Play the Basketball Roulette!

Try your luck at guessing where the ball is here and see if you can beat the algorithm!

References

What Players do with the Ball: A Physically Constrained Interaction Modeling

A. Maksai; X. Wang; P. Fua 

2016. International Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, Jun 26 – Jul 1 2016.

Take your Eyes off the Ball: Improving Ball-Tracking by Focusing on Team Play

X. Wang; V. H. Ablavsky; H. Ben Shitrit; P. Fua 

Computer Vision and Image Understanding. 2014. Vol. 119, p. 102-115. DOI : 10.1016/j.cviu.2013.11.010.