Three-dimensional vehicle pose estimation from two-dimensional monocular camera images for vehicle classification

In this paper, a new method is proposed to estimate the pose of a moving vehicle in a typical traffic scene. Pose determination is crucial in the process of fitting or matching an existing 3D model in the database with the captured moving object. In this work, pose estimation is determined by estimating the 3D position of the moving vehicle in world space and then computing the motion vector of the vehicle. The pose estimation is first initialized by loosely calibrating the camera viewport and the perspective distortion. The 3D position is then determined by computing the intersection of a ray trace of the vehicle's centroid obtained from the video image originating from the camera eye to the vehicle's motion plane, i.e. the ground. Once a motion vector is obtained, the 3D model is aligned to match the vehicle's pose. The computation is performed on a 3D graphics card. Results on real-world traffic scenes as well as synthetic data are presented and several issues are outlined.