Relative planar motion for vehicle-mounted cameras from a single affine correspondence

TL;DR

This paper introduces two novel solvers for estimating vehicle-mounted camera extrinsics from a single affine correspondence under planar motion assumptions, improving speed and accuracy over existing methods.

Contribution

It presents new minimal solvers for both semi-calibrated and fully calibrated cases, enabling fast and robust camera pose estimation from a single correspondence.

Findings

Methods outperform state-of-the-art in accuracy

Algorithms are faster and more robust in real datasets

Effective in long-distance vehicle-mounted camera scenarios

Abstract

Two solvers are proposed for estimating the extrinsic camera parameters from a single affine correspondence assuming general planar motion. In this case, the camera movement is constrained to a plane and the image plane is orthogonal to the ground. The algorithms do not assume other constraints, e.g.\ the non-holonomic one, to hold. A new minimal solver is proposed for the semi-calibrated case, i.e. the camera parameters are known except a common focal length. Another method is proposed for the fully calibrated case. Due to requiring a single correspondence, robust estimation, e.g. histogram voting, leads to a fast and accurate procedure. The proposed methods are tested in our synthetic environment and on publicly available real datasets consisting of videos through tens of kilometres. They are superior to the state-of-the-art both in terms of accuracy and processing time.