Abstract
We consider the self-calibration (affine and metric reconstruction) problem from images acquired with a camera with unchanging internal parameters undergoing planar motion. The general self-calibration methods (modulus constraint, Kruppa equations) are known to fail with this camera motion. In this paper we give two novel linear constraints on the coordinates of the plane at infinity in a projective reconstruction for any camera motion. In the planar case, we show that the two constraints are equivalent and easy to compute, giving us a linear version of the quartic modulus constraint. Using this fact, we present a new linear method to solve the self-calibration problem with planar motion of the camera from three or more images.
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This work was partly supported by project BFM2003-02914 from the Ministerio de Ciencia y Tecnología (Spain).
Ferran Espuny received the MSc in Mathematics in 2002 from the Universitat de Barcelona, Spain. He is currently a PhD student and associate professor in the Departament d’Àlgebra i Geometria at Universitat de Barcelona, Spain. His research, supervised by Dr. José Ignacio Burgos Gil, is focussed on self-calibration and critical motions for both pinhole and generic camera models.
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Espuny, F. A New Linear Method for Camera Self-Calibration with Planar Motion. J Math Imaging Vis 27, 81–88 (2007). https://doi.org/10.1007/s10851-006-9699-4
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DOI: https://doi.org/10.1007/s10851-006-9699-4