Abstract
We present a new external memory multiresolution surface representation for massive polygonal meshes. Previous methods for building such data structures have relied on resampled surface data or employed memory intensive construction algorithms that do not scale well. Our proposed representation combines efficient access to sampled surface data with access to the original surface. The construction algorithm for the surface representation exhibits memory requirements that are insensitive to the size of the input mesh, allowing it to process meshes containing hundreds of millions of polygons. The multiresolution nature of the surface representation has allowed us to develop efficient algorithms for view-dependent rendering, approximate collision detection, and adaptive simplification of massive meshes. The empirical performance of these algorithms demonstrates that the underlying data structure is a powerful and flexible tool for operating on massive geometric data.
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