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The paper presents a set of methods for multi view image tracking using a set of calibrated cameras. We demonstrate how effective the approach is for resolving occlusions and tracking objects between overlapping and non-overlapping camera views. Moving objects are initially detected using background subtraction. Temporal alignment is then performed between each video sequence in order to compensate for the different processing rates of each camera. A Kalman filter is used to track each object in 3D world coordinates and 2D image coordinates. Information is shared between the 2D/3D trackers of each camera view in order to improve the performance of object tracking and trajectory prediction. The system is shown to be robust in resolving dynamic and static object occlusions. Results are presented from a variety of outdoor surveillance video sequences.