Abstract:
|
Occlusion culling and level-of-detail rendering have
become two powerful tools for accelerating the handling of very large
models in real-time visualization applications. We present a framework
to combine both techniques that improves rendering times. Classical
occlusion culling algorithms compute potentially visible sets (PVS),
overestimations of the sets of visible polygons. The novelty of our
approach is to estimate the degree of visibility of each object of the
PVS using different level-of-detail for the occluders. This allows to
arrange the objects of each PVS into several Hardly-Visible Sets (HVS)
by similar occlusion percentage. According to image accuracy and frame
ratio requirements, HVS provide a way to avoid sending to the graphics
pipeline those objects whose pixel contribution is low due to partial
occlusion. The image loss can be bounded by the user at navigation
time. On the other hand, as HVS offers a tighter estimation of the
pixel contribution for each scene object it can be used for a more
convenient selection of the level-of-detail at which objects are
rendered.
In this paper, we describe the new framework technique, provide
details of its implementation using a visibility octree as the chosen
occlusion culling data structure and show some experimental results on
the image quality. |