3D tracking of a soccer ball using two synchronized cameras

We propose an adaptive method that can estimate 3D position of a soccer ball by using two viewpoint videos. The 3D position of a ball is essential to realize a 3D free viewpoint browsing system and to analyze of soccer games. At an image processing step, our method detects the ball by selecting the best algorithm based on the ball states so as to minimize the chance to miss the ball and to reduce the computation cost. The 3D position of the ball is then estimated by the estimated 2D positions of the two camera images. When it is impossible to obtain the 3D position due to the loss of the ball in an image, we utilize the Kalman Filter to compensate the missing position information and predict the 3D ball position. We implemented a preliminary system and succeeded in tracking the ball in 3D at almost on-line speed.