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We propose a method for calibrating the topology of distributed pan tilt cameras (i.e., the structure of routes among FOVs) and its probabilistic model, which is useful for multi-object tracking in a wide area. To observe objects as long and many as possible, pan tilt control is an important issue in automatic calibration as well as in tracking. If only one object is observed by a camera and its neighboring cameras, the camera should point towards this object both in the calibration and tracking periods. However, if there are multiple objects, in the calibration period, the camera should be controlled towards an object that goes through an unreliable route in which a sufficient number of object detection results have not been observed. This control allows us to efficiently establish the reliable topology model. After the reliable topology model is established, on the other hand, the camera should be directed towards the route with the biggest possibility of object observation. We therefore propose a camera control framework based on the mixture of the reliability of the estimated routes and the probability of object observation. This framework is applicable both to camera calibration and object tracking by adjusting weight variables. Experiments demonstrate the efficiency of our camera control scheme for establishing the camera topology model and tracking objects as long as possible.