Layer-based City Point Cloud Completion for Aerial Multi-view Reconstruction

Abstract

The method of using a drone to reconstruct a large-scale scene in 3D is a widely used method in 3D urban modeling. The specific process is to acquire an aerial multi-viewpoint image in the target city using a UAV (Unmanned Aerial Vehicle) and restore the 3D city point cloud model by matching the feature points. The aerial multi-viewpoint image obtained in this way requires sufficient overlap between adjacent images. Large-scale urban modeling takes a lot of time and effort because the UAV needs to fly to capture as much scene information as possible to reduce the effects of occlusion and noises. In this paper, we propose a layer-based point cloud complementation method that can extract the shape of an urban building and complement a scene with occlusion such as walls using only a small number of aerial ortho-mosaic views. The accuracy of the complementary result was verified by the city model acquired in the virtual reality space.