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Q.-T. Luong and O. Faugeras
ABSTRACT
We address the problem of estimating threedimensional motion, and structure from motion with an uncalibrated moving camera. We show that point correspondences between three im ages, and the fundamental matrices computed from these point correspondences, are suOEcient 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 3D structure up to a similarity. In contrast with other methods, no calibration object with a known 3D 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 deøne 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 ørst 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. 
ECVision indexed and annotated bibliography of cognitive computer vision publications
This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1
The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
Camera Calibration, Scene Motion and Structure Recovery from Point Correspondences and Fundamental MatricesSite generated on Friday, 06 January 2006