In this work, we develop image processing and computer vision techniques for visually tracking a tennis ball, in 3D, on a court instrumented with multiple low cost IP cameras. The technique first extracts 2D ball track data from each camera view, using object tracking methods. Next, an automatic feature- based video synchronization method is applied. This technique uses both the extracted 2D ball information from two or more camera views, plus camera calibration information. Then, in order to find 3D trajectory, the temporal 3D locations of the ball is estimated using triangulation of correspondent 2D locations obtained from automatically synchronized videos. Furthermore, we also incorporate a physics-based trajectory model into the system to improve the continuity of the tracked 3D ball during times when no two cameras have overlapping views of the ball location. The resultant 3D ball tracks are then visualized in a virtual 3D graphical environment. Finally, we quantify the accuracy of our system in terms of reprojection error.
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