Spatial data structures for accelerated 3D visibility computation to enable large model visualization on the web

The visualization of massive 3D models is an intensively examined field of research. Due to their rapidly growing complexity of such models, visualisation them in real-time will never be possible through a higher speed of rasterization alone. Instead, a practical solution has to reduce the amount of data to be processed, using a fast visibility determination. In recent years, the combination of Javascript and WebGL raised attention for the possibility of rendering hardware-accelerated 3D graphics directly in the browser. However, when compared to desktop applications, they are still fighting with their disadvantages of a generally slower execution speed, or a downgraded set of functionality. We demonstrate the integration of spatial data structures, computed on the client side, using latest technology trends to mitigate the shortcomings of the 3D Web environment. We employ comparably small bounding volume hierarchies to accelerate our visibility determination, as well as to enable specific culling techniques. This allows for an interactive visualization of such massive 3D data sets. Our in-depth analysis of different data structures and environments shows which combination of data structure and visibility determination techniques are currently the best fit for the Web.