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- W2109919481 abstract "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 a projective to a Euclidean structure by computing the projective distortion matrix in a way that is analogous to estimating the absolute quadric. Using singular value decomposition (SVD) as the main tool, and from a study of the ranks of the matrices involved in the process, we are able to enforce an accurate Euclidean reconstruction. Moreover, in contrast to other approaches, our process is essentially a linear one and does not require an initial estimation of the solution. Examples of synthetic and real data reconstructions are presented." @default.
- W2109919481 created "2016-06-24" @default.
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- W2109919481 date "2005-08-25" @default.
- W2109919481 modified "2023-09-22" @default.
- W2109919481 title "Recovering 3D metric structure and motion from multiple uncalibrated cameras" @default.
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- W2109919481 doi "https://doi.org/10.1109/itcc.2002.1000399" @default.
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