"Spectral Processing of Point-Sampled Geometry"

surface models that contain hundreds of millions of sample points. I will
present
a new framework for processing such point-sampled objects using spectral
methods. By establishing a concept of local frequencies on geometry, a
versatile spectral representation is introduced that provides a rich
repository of signal processing algorithms. The algorithm 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. Applications
include noise removal, enhancement, restoration and subsampling of
point-sampled geometric models."