Relative planar motion for vehicle-mounted cameras from a single affine correspondence
This work addresses vehicle-mounted camera calibration for applications like autonomous driving or robotics, representing an incremental improvement in efficiency and accuracy over existing methods.
The paper tackles the problem of estimating extrinsic camera parameters from a single affine correspondence under general planar motion constraints, proposing two solvers for semi-calibrated and fully calibrated cases. The methods achieve superior accuracy and processing time compared to state-of-the-art approaches, as validated on synthetic and real-world datasets spanning tens of kilometers.
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.