Multiple camera based surveillance systems provide us with a more robust tracking of objects. To take advantage of additional cameras, it is necessary to establish geometrical relationship between the cameras and relationship between an object and a camera. In recent years several techniques have been proposed, which estimate only the relation of a dominant ground plane between different views instead of fully geometrical relation of cameraobject-camera. They are however neither fully automatic nor suitable for a non-planar ground. We propose a fully automatic calibration algorithm which can cope with complex environment, including non-planar ground. The proposed algorithm automatically tracks and matches objects between different views, determines the overlapped region, and aligns each piece-wisely segmented plane between two views. The proposed calibration algorithm minimizes the effect of occlusion and improves the accuracy of 3D measurements by using multiple views. The algorithm can also provide us large field of view by concatenating a series of cameras.

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