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Self-Calibration and Euclidean Reconstruction Using Motions of A Stereo Rig

Radu Horaud 1 Gabriela Csurka 1 
1 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : This paper describes a method to upgrade projective reconstruction to affine and to metric reconstructions using rigid general motions of a stereo rig. We make clear the algebraic relationships between projective reconstruction, the plane at infinity (affine reconstruction), camera calibration, and metric reconstruction. We show that all the computations can be carried out using standard linear resolution methods and that these methods compare favorably with nonlinear optimization, methods in the presence of Gaussian noise. We carry out a theoretical error analysis which quantify the relative importance of the accuracies of projective-to-affine conversion and affine-to-Euclidean conversion. Experiments with with real data are consistent with the theoretical error analysis and with a sensitivity analysis performed with simulated data.
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Submitted on : Tuesday, May 3, 2011 - 9:18:34 AM
Last modification on : Wednesday, May 4, 2022 - 12:12:03 PM
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Radu Horaud, Gabriela Csurka. Self-Calibration and Euclidean Reconstruction Using Motions of A Stereo Rig. 6th International Conference on Computer Vision (ICCV '98), Jan 1998, Bombay, India. pp.96--103, ⟨10.1109/ICCV.1998.710706⟩. ⟨inria-00590095⟩



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