Basketball self training shooting posture recognition and trajectory estimation using computer vision and Kalman filter

Yunus Egi

   Self-shooting training is one of the fundamental criteria for success in basketball. Particularly, young players increase their performance with regular training. However, the training process becomes painful and time-consuming without a coach since the incorrect shooting posture causes missing shots, leading to reluctance. In this research, a self-shooting posture algorithm is developed to track the movement of basketball players and give them feedback about their position, angle, and basketball projectile trajectory information. The proposed algorithm uses computer vision techniques and Kalman filter to detect the best projectile trajectory using initial conditions such as acceleration due to gravity

Keywords: posture recognition, image processing, projectile trajectory estimation, basketball, Kalman filter

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