Out-of-core real-time visualization of massive 3D point clouds

This paper presents a point-based rendering approach to visualize massive sets of 3D points in real-time. In many disciplines such as architecture, engineering, and archeology LiDAR technology is used to capture sites and landscapes; the resulting massive 3D point clouds pose challenges for traditional storage, processing, and presentation techniques. The available hardware resources of CPU and GPU are limited, and the 3D point cloud data exceeds available memory size in general. Hence out-of-core strategies are required to overcome the limit of memory. We discuss concepts and implementations of rendering algorithms and interaction techniques that make out-of-core real-time visualization and exploration of massive 3D point clouds feasible. We demonstrate with our implementation real-time visualization of arbitrarily sized 3D point clouds with current PC hardware using a spatial data structure in combination with a point-based rendering algorithm. A rendering front is used to increase the performance taking into account user interaction as well as available hardware resources. Furthermore, we evaluate our approach, describe its characteristics, and report on applications.