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Erratum published on 23 June 2017, see J. Imaging 2017, 3(3), 23.
Open AccessArticle

Radial Distortion from Epipolar Constraint for Rectilinear Cameras

1
Department of Built Environment, Aalto University, P.O. Box 15800, 00076 Aalto, Finland
2
National Land Survey of Finland, Finnish Geospatial Research Institute FGI, PL 84, 00521 Helsinki, Finland
*
Author to whom correspondence should be addressed.
Academic Editor: Gonzalo Pajares Martinsanz
J. Imaging 2017, 3(1), 8; https://doi.org/10.3390/jimaging3010008
Received: 10 August 2016 / Revised: 11 January 2017 / Accepted: 13 January 2017 / Published: 24 January 2017
Lens distortion causes difficulties for 3D reconstruction, when uncalibrated image sets with weak geometry are used. We show that the largest part of lens distortion, known as the radial distortion, can be estimated along with the center of distortion from the epipolar constraint separately and before bundle adjustment without any calibration rig. The estimate converges as more image pairs are added. Descriptor matched scale-invariant feature (SIFT) point pairs that contain false matches can readily be given to our algorithm, EPOS (EpiPOlar-based Solver), as input. The processing is automated to the point where EPOS solves the distortion whether its type is barrel or pincushion or reports if there is no need for correction. View Full-Text
Keywords: lens distortion; radial distortion; center of distortion; camera calibration; epipolar constraint; relative pose; fundamental matrix lens distortion; radial distortion; center of distortion; camera calibration; epipolar constraint; relative pose; fundamental matrix
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MDPI and ACS Style

Lehtola, V.V.; Kurkela, M.; Rönnholm, P. Radial Distortion from Epipolar Constraint for Rectilinear Cameras. J. Imaging 2017, 3, 8.

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