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Multiresolution Distance Volumes for Progressive Surface Compression.

DE200515013487

Publication Date	2002
Personal Author	Laney, D. E.; Bertram, M.; Duchaineau, M. A.; Max, N. L.
Page Count	18
Abstract	We present a surface compression method that stores surfaces as wavelet-compressed signed-distance volumes. Our approach enables the representation of surfaces with complex topology and arbitrary numbers of components within a single multiresolution data structure. This data structure elegantly handles topological modification at high compression rates. Our method does not require the costly and sometimes infeasible base mesh construction step required by subdivision surface approaches. We present several improvements over previous attempts at compressing signed-distance functions, including an 0 (n) distance transform, a 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.
Keywords	Topology Computational grids Algorithms Thresholds Surfaces Multiresolution analysis
Source Agency	Technical Information Center Oak Ridge Tennessee
Corporate Authors	Lawrence Livermore National Lab., CA.; Department of Energy, Washington, DC.
Supplemental Notes	Sponsored by Department of Energy, Washington, DC.
Document Type	Technical Report
NTIS Issue Number	200601

Multiresolution Distance Volumes for Progressive Surface Compression.

Multiresolution Distance Volumes for Progressive Surface Compression.
DE200515013487

Publication Date	2002
Personal Author	Laney, D. E.; Bertram, M.; Duchaineau, M. A.; Max, N. L.
Page Count	18
Abstract	We present a surface compression method that stores surfaces as wavelet-compressed signed-distance volumes. Our approach enables the representation of surfaces with complex topology and arbitrary numbers of components within a single multiresolution data structure. This data structure elegantly handles topological modification at high compression rates. Our method does not require the costly and sometimes infeasible base mesh construction step required by subdivision surface approaches. We present several improvements over previous attempts at compressing signed-distance functions, including an 0 (n) distance transform, a 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.
Keywords	Topology Computational grids Algorithms Thresholds Surfaces Multiresolution analysis
Source Agency	Technical Information Center Oak Ridge Tennessee
Corporate Authors	Lawrence Livermore National Lab., CA.; Department of Energy, Washington, DC.
Supplemental Notes	Sponsored by Department of Energy, Washington, DC.
Document Type	Technical Report
NTIS Issue Number	200601