  This paper proposes minimal solvers that use combinations of imaged
translational symmetries and parallel scene lines to jointly estimate lens
undistortion with either affine rectification or focal length and absolute
orientation. We use constraints provided by orthogonal scene planes to recover
the focal length. We show that solvers using feature combinations can recover
more accurate calibrations than solvers using only one feature type on scenes
that have a balance of lines and texture. We also show that the proposed
solvers are complementary and can be used together in a RANSAC-based estimator
to improve auto-calibration accuracy. State-of-the-art performance is
demonstrated on a standard dataset of lens-distorted urban images. The code is
available at https://github.com/ylochman/single-view-autocalib.
