Calibrating Freely Moving Cameras

We present a novel practical method for self-calibrating a camera which may move freely in space while changing it internal parameters by zooming. We show that point correspondences between a pair of images, and the fundamental matrix computed from these point correspondences, are sufficient to recover the internal parameters of a camera. Unlike other methods, no calibration object with known 3D shape is required and no limitations are put on the unknown motion, as long as the camera is projective. The main contribution of this paper is development of a global linear solution which is based on the well-known Kruppa equations. We introduce a formulation different from the Huang and Faugeras constraints. The method has been extensively tested on synthetic and real data and promising results are reported

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