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Minimal Solvers for Rectifying from Radially-Distorted Conjugate Translations

4 November 2019
James Pritts
Zuzana Kukelova
Viktor Larsson
Yaroslava Lochman
Ondřej Chum
ArXiv (abs)PDFHTML
Abstract

This paper introduces minimal solvers that jointly solve for affine-rectification and radial lens undistortion 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 local feature types and sampling strategies, and three of the proposed variants can jointly recover rectification and lens undistortion from just one local 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 confirm that the proposed solvers demonstrate superior robustness to noise compared to the state of the art. The solvers are integrated into a fully-automated system for rectifying imaged scene planes from coplanar repeated texture. Accurate rectifications on challenging imagery taken with narrow to fisheye field-of-view lenses demonstrate the wide applicability of the proposed methods.

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