BetterSight: Immersive Vision Training for Basketball Players

Abstract

Vision training is important for athletes and is key to win a sports game. Traditional vision training methods are suitable for sports that focus only on the ball. For basketball, however, players need to observe multiple moving objects (i.e., ball and players) concurrently on a large court. We propose BetterSight, an immersive vision training system for basketball that not only trains the vision of the player but also requires the player to dribble the ball stably, mimicking the situation in a real basketball game. BetterSight is composed of an Interaction Module (IM), a Training Content Generation Module (TCGM), and an Analysis Module (AM). IM allows the trainee to interact with the system more intuitively based on gesture and speech rather than the controller. TCGM simulates the training scenarios based on the training configurations selected by the trainee. AM collects the video sequences capturing the trainee and the trainee's eye movements during the training phase, and then analyzes the trainee's gaze, dribbling movements, and number of dribbles. The analyzed data can be used to evaluate the training effectiveness of using the proposed BetterSight.