A Point-Based and Image-Based Multi-Pass Rendering Technique for Visualizing Massive 3D Point Clouds in VR Environments

Real-time rendering for 3D point clouds allows for interactively exploring and inspecting real-world assets, sites, or regions on a broad range of devices but has to cope with their vastly different computing capabilities. Virtual reality (VR) applications rely on high frame rates (i.e., around 90 fps as opposed to 30 -60 fps) and show high sensitivity to any kind of visual artifacts, which are typical for 3D point cloud depictions (e.g., holey surfaces or visual clutter due to inappropriate point sizes). We present a novel rendering system that allows for an immersive, nausea-free exploration of arbitrary large 3D point clouds on state-of-the-art VR devices such as HTC Vive and Oculus Rift. Our approach applies several point-based and image-based rendering techniques that are combined using a multipass rendering pipeline. The approach does not require to derive generalized, mesh-based representations in a preprocessing step and preserves precision and density of the raw 3D point cloud data. The presented techniques have been implemented and evaluated with massive real-world data sets from aerial, mobile, and terrestrial acquisition campaigns containing up to 2.6 billion points to show the practicability and scalability of our approach.