Abstract
A plane approximation-based approach for 3D reconstruction of ball trajectory is introduced, which was developed as a solution to the problem with conventional analysis in table tennis. There are methods of reconstructing 2D ball trajectories or 3D trajectories of balls heavier than those in table tennis. However, these methods cannot be adopted to reconstruct the 3D trajectories of table tennis balls, because there are problems that are attributed to the dimensions of the trajectories and weight of the balls. The method proposed in this chapter could reconstruct the 3D trajectories of a table tennis ball. The key feature of the method is that it approximates that a ball is traveling on tilted planes. This approximation makes reconstruction robust against failure to measure 3D ball positions. Two systems were developed based on the new method. A system using two RGB cameras experimentally demonstrated that it could provide accurate information for match analysis. A system using an RGB-D camera was experimentally demonstrated that the system could provide accurate information for service analysis.
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Notes
- 1.
Shot number denotes the ordinal number of shots in a rally. For example, making the serve is the first, and receiving it is the second.
- 2.
Players making serves in table tennis need to bounce the ball in their own court before they bounce it in the opposite court. It is therefore difficult to score by increasing the velocity of the ball. This is why many players mainly consider tactics with rotation and direction when serving.
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Acknowledgments
This work is supported by National Institute of Information and Communications Technology (NICT), Japan. We would also like to express our gratitude to Jun Nakamura for his contribution in developing and experiments of the system using an RGB-D camera.
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Tamaki, S., Saito, H. (2014). Plane Approximation-Based Approach for 3D Reconstruction of Ball Trajectory for Performance Analysis in Table Tennis. In: Moeslund, T., Thomas, G., Hilton, A. (eds) Computer Vision in Sports. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-319-09396-3_3
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