Ground Camera Images and UAV 3D Model Registration for Outdoor Augmented Reality

This paper presents a novel virtual-real registration approach for augmented reality (AR) in large-scale outdoor environments. Essentially, it is a pose estimation for the mobile camera images (ground camera images) in 3D model recovered by Unmanned Aerial Vehicle (UAV) image sequence via Structure-From-Motion (SFM) technology. The approach considers to indirectly establish the spatial relationship between 2D and 3D space by inferring the transformation relationship between the ground camera images and the UAV 3D model rendered images. Specifically, the proposed approach can overcome the positioning errors, which are deterioration and drift in the GPS, and deviation of orientation. The experimental results demonstrate the possibility of the proposed virtual-real registration approach, and show that the approach is robust, efficient and intuitive for AR in large-scale outdoor environments.