Camera Calibration, Scene Motion and Structure recovery from point correspondences and fundamental m

We address the problem of estimating three-dimensional motion, and structure from motion with an uncalibrated moving camera. We show that point correspondences between three images , and the fundamental matrices computed from these point correspondences, are suucient to recover the internal orientation of the camera (its calibration), the motion parameters, and to compute coherent perspective projection matrices which enable us to reconstruct 3-D structure up to a similarity. In contrast with other methods, no calibration object with a known 3-D shape is needed, and no limitations are put upon the unknown motions to be performed or the parameters to be recovered, as long as they deene a projective camera. The theory of the method, which is based on the constraint that the observed points are part of a static scene, thus allowing us to link the intrinsic parameters and the fundamental matrix via the absolute conic, is rst detailed. Several algorithms are then presented, and their performances compared by means of extensive simulations. An application of the method to a binocular or trinocular stereo rig is also considered. It is illustrated by several experiments with real images which conclude the paper.

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