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Mark Pauly, Markus Gross, Spectral Processing of Point-Sampled Geometry, Proceedings of Siggraph 2001
Abstract:
We present a new framework for processing point-sampled objects
using spectral methods. By establishing a concept of local frequencies
on geometry, we introduce a versatile spectral representation
that provides a rich repository of signal processing algorithms.
Based on an adaptive tesselation of the model surface into regularly
resampled displacement fields, our method computes a set of
windowed Fourier transforms creating a spectral decomposition of
the model. Direct analysis and manipulation of the spectral coefficients
supports effective filtering, resampling, power spectrum
analysis and local error control. Our algorithms operate directly on
points and normals, requiring no vertex connectivity information.
They are computationally efficient, robust and amenable to hardware
acceleration. We demonstrate the performance of our framework
on a selection of example applications including noise
removal, enhancement, restoration and subsampling.
Bibtex:
@inproceedings{pg-sppsg-01,
author = {Mark Pauly and Markus Gross},
title = {Spectral Processing of Point-Sampled Geometry},
booktitle = {Proceedings of Siggraph },
year = {2001},
}
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