Multiresolution Distance Volumes for Progressive Surface Compression
Surfaces generated by scientific simulation and range scanning can reach into the billions of polygons. Such surfaces must be aggressively compressed, but at the same time should provide for level of detail queries. Progressive compression techniques based on subdivision surfaces produce impressive results on range scanned models. However, these methods require the construction of a base mesh which parameterizes the surface to be compressed and encodes the topology of the surface. For complex surfaces with high genus and/or a large number of components, the computation of an appropriate base mesh is difficult and often infeasible. We present a surface compression method that stores surfaces as wavelet-compressed signed-distance volumes. Our method avoids the costly base-mesh construction step and offers several improvements over previous attempts at compressing signed-distance functions, including an {Omicron}(n) distance transform, a new zero set initialization method for triangle meshes, and a specialized thresholding algorithm. We demonstrate the potential of sampled distance volumes for surface compression and progressive reconstruction for complex high genus surfaces.
- Research Organization:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- US Department of Energy (US)
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 15005935
- Report Number(s):
- UCRL-JC-146852; TRN: US200402%%222
- Resource Relation:
- Conference: 1st International Symposium on 3D Data Processing Visualization and Transmission, Padova (IT), 06/19/2002--06/21/2002; Other Information: PBD: 14 Jan 2002
- Country of Publication:
- United States
- Language:
- English
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