Model-based Camera 3D Pose Tracking – A Solution of Registration Problem for On-Road Navigation

Z. Hu and K. Uchimura (Japan)


Registration problem, Augmented Reality, Onroad navigation, camera pose estimation, road model matching


This paper presents dynamical 3D pose estimation and tracking method for a camera mounted on the moving passenger car. Tracking of on-board camera’s position and orientation plays a key role in solving the registration problem of Augmented Reality (AR). Especially in our Vision-based Car Navigation System (VICNAS), a new concept of on-road navigation, camera pose estimation becomes the most essential technique for properly superimposing the synthetic virtual objects like navigation arrows and road information labels into the real road scene. Traditional camera pose estimation algorithms always need to have a fixed and known-structure model as well as the object depth information to obtain the 3D-2D correlations, which is not possible in the case of on-road driving. With the constraints of road structure and on-road vehicle motion features, this paper presents a new efficient pose tracking algorithm, which converts the problem of 3D-2D points correlation to the 2D-2D road model matching on projective image. We proposed a multi-lane road model generation method based on the 2D digital road map and the absolute position data obtained from GPS and Inertial sensors. Additional road shape lookup table (RSL) concept is also presented in this paper to calculate the road model matching score. The algorithms proposed in this paper are validated with the experimental results from real road test under different conditions and types of road.

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