The Randomized Sample Tree: A Data Structure for Interactive Walk-Throughs in Externally Stored Virtual Environments

We present a new data structure for rendering highly complex virtual environments of arbitrary topology. The special feature of our approach is that it allows an interactive navigation in very large scenes (30 GB/400 million polygons in our benchmark scenes) that cannot be stored in main memory, but only on a local or remote hard disk. Furthermore, it allows interactive rendering of substantially more complex scenes by instantiating objects. The sampling process is done in the preprocessing. There, the polygons are randomly distributed in our hierarchical data structure, the randomized sample tree. This tree only uses space that is linear in the number of polygons. In order to produce an approximate image of the scene, the tree is traversed and polygons stored in the visited nodes are rendered. During the interactive walkthrough, parts of the sample tree are loaded from local or remote hard disk. We implemented our algorithm in a prototypical walkthrough system. Analysis and experiments show that the quality of our images is comparable to images computed by the conventional z-buffer algorithm regardless of the scene topology.