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Mark Pauly, Markus Gross, Leif Kobbelt, Efficient Simplification of Point-Sampled Surfaces, Proceedings of IEEE Visualization 2002
Abstract:
In this paper we introduce, analyze and quantitatively compare a
number of surface simplification methods for point-sampled
geometry. We have implemented incremental and hierarchical
clustering, iterative simplification, and particle simulation algorithms
to create approximations of point-based models with lower
sampling density. All these methods work directly on the point
cloud, requiring no intermediate tesselation. We show how local
variation estimation and quadric error metrics can be employed to
diminish the approximation error and concentrate more samples in
regions of high curvature. To compare the quality of the simplified
surfaces, we have designed a new method for computing numerical
and visual error estimates for point-sampled surfaces. Our
algorithms are fast, easy to implement, and create high-quality surface
approximations, clearly demonstrating the effectiveness of
point-based surface simplification.
Bibtex:
@inproceedings{pgk-espss-02,
author = {Mark Pauly and Markus Gross and Leif Kobbelt },
title = {Efficient Simplification of Point-Sampled Surfaces},
booktitle = {Proceedings of IEEE Visualization },
year = {2002},
}
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