Minimal Solvers for Rectifying From Radially-Distorted Conjugate Translations

This paper introduces minimal solvers that jointly solve for radial lens undistortion and affine-rectification using local features extracted from the image of coplanar translated and reflected scene texture, which is common in man-made environments. The proposed solvers accommodate different types...

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Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 2021-11, Vol.43 (11), p.3931-3948
Main Authors: Pritts, James, Kukelova, Zuzana, Larsson, Viktor, Lochman, Yaroslava, Chum, Ondrej
Format: Article
Language:English
Subjects:
Cameras
Distortion
Feature extraction
Field of view
Geometry
Lenses
local features
minimal solvers
Parallel processing
radial distortion
Rectification
repeated patterns
Solvers
symmetry
Texture
Translations
Transmission line matrix methods
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Summary:This paper introduces minimal solvers that jointly solve for radial lens undistortion and affine-rectification using local features extracted from the image of coplanar translated and reflected scene texture, which is common in man-made environments. The proposed solvers accommodate different types of local features and sampling strategies, and three of the proposed variants require just one feature correspondence. State-of-the-art techniques from algebraic geometry are used to simplify the formulation of the solvers. The generated solvers are stable, small and fast. Synthetic and real-image experiments show that the proposed solvers have superior robustness to noise compared to the state of the art. The solvers are integrated with an automated system for rectifying imaged scene planes from coplanar repeated texture. Accurate rectifications on challenging imagery taken with narrow to wide field-of-view lenses demonstrate the applicability of the proposed solvers.
ISSN:0162-8828
1939-3539
2160-9292
DOI:10.1109/TPAMI.2020.2992261