When a table tennis ball is hit by a racket, the ball spins and undergoes a complex trajectory in the air. In this article, a model of a spinning ball is proposed for simulating and predicting the ball flight trajectory including the topspin, backspin, rightward spin, leftward spin, and combined spin. The actual trajectory and rotational motion of a flying ball are captured by three high-speed cameras and then reconstructed using a modified vision tracking algorithm. For the purpose of model validation, the simulated trajectory is compared to the reconstructed trajectory, resulting in a deviation of only 2.42%. Such high modeling accuracy makes this proposed method an ideal tool for developing the virtual vision systems emulating the games that can be used to train table tennis players efficiently.
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