Vehicle Pose Estimation Based on Edge Distance Using Lidar Point Clouds (Poster)

Vehicle pose estimation plays an significant role in vehicle tracking which is an important part in autonomous driving. In this paper, a new vehicle pose estimation method based on Edge Distance is proposed. The Edge Distance is defined to describe the distribution of point clouds with respect to their bounding rectangles. Based on the Edge Distance, a bounding rectangle of the point clouds is utilized to fit the vehicle outline. For the case where the point clouds are sparse or only one edge is visible, the bounding rectangle is modified according to preset vehicle size. The pose estimation of the vehicle is obtained based on the bounding rectangle. Experiments based on the KITTI data sets show that the proposed method can obtain better performance in vehicle pose estimation compared with the method based on modified scaling series.