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This paper proposes a method for offline accurate ball tracking for short volleyball actions in sport halls. Our aim is to detect block touches on the ball and to determinate accurate trajectory and impact positions of the ball to support referees. The proposed method is divided into two stages, namely training and ball tracking, and is based on background subtraction. Application of the Gaussian mixture model has been used to estimate a background, and a high-speed camera with a capture rate of 180 frames per second and a resolution of 1920 × 1080 are used for motion capture. In sport halls significant differences in light intensity occur between each sequence frame. To minimize the influence of these light changes, an additional model is created and template matching is used for accurate determination of ball positions when the ball contour in the foreground image is distorted. We show that this algorithm is more accurate than other methods used in similar systems. Our light intensity change model eliminates almost all pixels added to images of moving objects owing to sudden changes in intensity. The average accuracy achieved in the validation process is of 0.57 pixel. Our algorithm accurately determined 99.8% of all ball positions from 2000 test frames, with 25.4 ms being the average time for a single frame analysis. The algorithm presented in this paper is the first stage of referee support using a system of many cameras and 3D trajectories.