Development and comparison of homography based estimation techniques for camera to road surface orientation

This paper focuses on dynamic orientation estimation of a vehicle-mounted mono camera. In particular, the pitch and roll angles of the camera relative to the road surface. Information about the orientation angles is included in the homography (projective transformation) between two images of a planar road surface. The extraction of angles from a homography matrix is possible but not recommended due to parameter ambiguities. For this reason we do not estimate a full homography matrix but reduce the parameter space to two parameters. In this area of parameter estimation there are mainly two different approaches: The optical flow based approach and the image registration based approach. In order to decide which of these approaches is more favorable for the angle estimation problem, we develop one optical flow based and one image registration based angle estimation algorithm. We are the first directly evaluating and comparing both approaches with each other with the help of an artificial image sequence as well as real-world driving scenarios. In addition, this paper lifts the common limitation of roll angle of zero degree for dynamic camera orientation estimation. Our research finds that there is only a small difference between the parameter estimation results of the optical flow and image registration based approach.