Small Ball Tracking with Trajectory Prediction
Shambel Ferede, Xuemei Xie, Chen Bo Calvin Zhang, Jiang Du, Guangming Shi · 2020
We propose small ball tracking with trajectory prediction to track them when the athletes playing with balls at sports field, as shown in Figure 1. This is a challenging task and important for intelligent physical education, especially for the coaches to grasp the accuracy of actions by the players based on the pre-defined rules. The proposed method achieves a good performance on small ball tracking since the designed algorithm incorporates motion, temporal and directional information to predict the trajectory. Experimental results show that the proposed method effectively reduces the number of identity switches and decreases track fragmentation. With the integration of motion, directional information and frames storage, this framework efficiently track small balls when the athletes playing with them.