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Calibration in a multi camera network has widely been studied for overseveral years starting from the earlier days of photogrammetry. Many authorshave presented several calibration algorithms with their relative advantagesand disadvantages. In a stereovision system, multiple view reconstruction is achallenging task. However, the total computational procedure in detail has notbeen presented before. Here in this work, we are dealing with the problem that,when a world coordinate point is fixed in space, image coordinates of that 3Dpoint vary for different camera positions and orientations. In computer visionaspect, this situation is undesirable. That is, the system has to be designedin such a way that image coordinate of the world coordinate point will be fixedirrespective of the position & orientation of the cameras. We have done it inan elegant fashion. Firstly, camera parameters are calculated in its localcoordinate system. Then, we use global coordinate data to transfer all localcoordinate data of stereo cameras into same global coordinate system, so thatwe can register everything into this global coordinate system. After all thetransformations, when the image coordinate of the world coordinate point iscalculated, it gives same coordinate value for all camera positions &orientations. That is, the whole system is calibrated.

Multiple View Reconstruction of Calibrated Images using Singular Value Decomposition