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Recovering 3D metric structure and motion from multiple uncalibrated cameras
Proceedings. International Conference on Information Technology: Coding and Computing
An optimized linear factorization method for recovering both the 3D geometry of a scene and the camera parameters from multiple uncalibrated images is presented. In a first step, we recover a projective approximation using a well known iterative approach. Then, we are able to upgrade from projective to Euclidean structure by computing the projective distortion matrix in a way that is analogous to estimating the absolute quadric. Using the Singular Value Decomposition (SVD) as a main tool, and
doi:10.1109/itcc.2002.1000399
dblp:conf/itcc/SainzBS02
fatcat:wll7tiib5vanrmfvkxyvkrvfze