Out-of-Core Simplification with Guaranteed Error Tolerance
Abstract
In this paper we present a high quality end-to-end out-of-core mesh simplification algorithm that is capable to guarantee a given geometric error compared to the original model.
The method consists of three parts: memory insensitive cutting; hierarchical simplification; memory insensitive stitching of adjacent parts. Since the first and last part of the algorithm work entirely on disk and the number of vertices during each simplification step is bound by a constant value, the whole algorithm can process models that are far too large to fit into memory.
In contrast to most previous out-of-core we do not use vertex clustering since for a given error tolerance the reduction rates are low compared to vertex contraction techniques. Since we use a high quality simplification method during the whole reduction and we guarantee a maximum geometric error between the original and simplified model, the computation time is higher compared to recent approaches, but the gain in quality and/or reduction rate is significant.
Stichwörter: mesh simplification, out-of-core algorithms
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Bibtex
@INPROCEEDINGS{borodin-2003-out-of-core, author = {Borodin, Pavel and Guthe, Michael and Klein, Reinhard}, editor = {Ertl, T. and Girod, B. and Greiner, G. and Niemann, H. and Seidel, H.-P. and Steinbach, E. and Westermann, R.}, pages = {309--316}, title = {Out-of-Core Simplification with Guaranteed Error Tolerance}, booktitle = {Vision, Modeling and Visualisation 2003}, year = {2003}, month = nov, publisher = {Akademische Verlagsgesellschaft Aka GmbH, Berlin}, keywords = {mesh simplification, out-of-core algorithms}, abstract = {In this paper we present a high quality end-to-end out-of-core mesh simplification algorithm that is capable to guarantee a given geometric error compared to the original model. The method consists of three parts: memory insensitive cutting; hierarchical simplification; memory insensitive stitching of adjacent parts. Since the first and last part of the algorithm work entirely on disk and the number of vertices during each simplification step is bound by a constant value, the whole algorithm can process models that are far too large to fit into memory. In contrast to most previous out-of-core we do not use vertex clustering since for a given error tolerance the reduction rates are low compared to vertex contraction techniques. Since we use a high quality simplification method during the whole reduction and we guarantee a maximum geometric error between the original and simplified model, the computation time is higher compared to recent approaches, but the gain in quality and/or reduction rate is significant.}, isbn = {3-89838-048-3}, conference = {The 8th International Fall Workshop Vision, Modeling and Visualisation 2003} }