mlsanityData to 14 Oct 2026

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

arXiv 1511.06181 ↗First posted 19 Nov 2015cs.CVcited by 17

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Abstract (arXiv)

Tracking the ball is critical for video-based analysis of team sports. However, it is difficult, especially in low-resolution images, due to the small size of the ball, its speed that creates motion blur, and its often being occluded by players. In this paper, 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.

Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). First posted on arXiv 19 Nov 2015.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 2; 2022: 4; 2023: 7; 2024: 0; 2025: 3; 2026: 1.

17 papers.

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  1. 2021Learning Dynamics via Graph Neural Networks for Human Pose Estimation and Trackingcited by 37
  2. 2022A Survey on Video Action Recognition in Sports: Datasets, Methods and Applicationscited by 28
  3. 2022A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directionscited by 21
  4. 2022Ball 3D Localization From A Single Calibrated Imagecited by 17
  5. 2021Online Multiple Object Tracking with Cross-Task Synergycited by 12
  6. 2023Ball Trajectory Inference from Multi-Agent Sports Contexts Using Set Transformer and Hierarchical Bi-LSTMcited by 12
  7. 2023Hang-Time HAR: A Benchmark Dataset for Basketball Activity Recognition using Wrist-Worn Inertial Sensorscited by 11
  8. 2023A Survey of Deep Learning in Sports Applications: Perception, Comprehension, and Decisioncited by 11
  9. 2025Towards Ball Spin and Trajectory Analysis in Table Tennis Broadcast Videos via Physically Grounded Synthetic-to-Real Transfercited by 4
  10. 2022Optical tracking in team sportscited by 3
  11. 2023Towards Learning Monocular 3D Object Localization From 2D Labels using the Physical Laws of Motioncited by 3
  12. 2025Uplifting Table Tennis: A Robust, Real-World Application for 3D Trajectory and Spin Estimationcited by 3
5 more
  1. 2023Context-Aware 3D Object Localization from Single Calibrated Images: A Study of Basketballscited by 2
  2. 2023Visualizing Skiers' Trajectories in Monocular Videoscited by 1
  3. 2023Towards Real-Time Analysis of Broadcast Badminton Videoscited by 0
  4. 2025Real-time Localization of a Soccer Ball from a Single Cameracited by 0
  5. 2026PathCRF: Ball-Free Soccer Event Detection via Possession Path Inference from Player Trajectoriescited by 0