Onboard camera pose estimation in augmented reality space for direct visual navigation

This paper presents a dynamical solution of the registration problem for on-road navigation applications via 3D-2D parameterized model matching algorithm. Traditional camera’s three dimensional (3D) position and pose estimation algorithms always employ the fixed and known-structure models as well as the depth information to obtain the 3D-2D correlations, which is however unavailable for on-road navigation applications since there are no fixed models in the general road scene. With the constraints of road structure and on-road navigation features, this paper presents a 2D digital road map based road shape modeling algorithm. Dynamically generated multi-lane road shape models are used to match real road scene to estimate camera 3D position and pose data. Our algorithms successfully simplified the 3D-2D correlation problem to the 2D-2D road model matching on the projective image. The algorithms proposed in this paper are validated with the experimental results from real road test under different conditions and types of road.