|System flowchart Our result CAMShift wrong tracking result Confusion matrix of recognizing grade rate||
For beginners, basketball dribbling training requires instructions from coaches. To ensure the training is effective, coaches usually teach details and emphases of each move and correct mistakes right away as a bystander. Then, they might just need training videos to practice autonomously, but the correctness of moves is not able to confirm objectively. Therefore, we present a Kinect-based assistance system for user to train autonomously at home or community centers no matter when. Moreover, our system is able to provide visual feedback of each move in real-time to ensure the correctness. We can get user’s skeleton information by using Kinect and Kinect skeletal tracking algorithm. We can also automatically detect basketball and get its location in real-time by improving existing object detect and tracking algorithm with color, depth, and body index images obtained from Kinect. For posture recognition, we separated dribble moves into details and emphases, defined these as independent postures, and built posture database by using a machine learning based tool－Microsoft Visual Gesture Builder. By combining skeleton, ball locations, and posture recognition, we can achieve our goal. Our system solves problems such as no coach as bystander or no objective confirmation of correctness of moves. Note that our system does not aim to replace conventional role of coaches, but to allow players and coaches to have more time flexibility. In addition, our system can be applied to serve a basketball team. Coach decides training menu, emphases of moves, and passing standard for each player and gets reports after players finish their training. Therefore, coach can teach more players at once, and player can choose when he/she wants to train in a time limit.