Level-of-detail occlusion culling is a novel approach to the management of occluders that can be easily integrated into most current visibility culling algorithms. The main contribution of this paper is an algorithm that automatically generates sets of densely overlapping boxes with enhanced occlusion properties from non-convex subsets. We call this method occluder synthesis because it is not sensitive to the way the objects are tesselated but to the space enclosed by them. The extension of this technique by allowing a bounded amount of image error is also discussed. We show that visibility computations can be based on a multiresolution model which provides several representations of these occluders with varying visibility accuracy. Our tests show that occlusion performance in tesselated scenes is improved severely even if no image-error is allowed.
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