| Abstract |
Abstract Defining sharp features
in a 3D model facilitates a better
understanding of the surface and aid
geometric processing and graphics
applications, such as reconstruction,
filtering, simplification, reverse
engineering, visualization, and
non-photo realism. We present
a robust method that identifies sharp
features in a point-based model by
returning a set of smooth spline
curves aligned along the edges.
Our feature extraction leverages
the concepts of robust moving
least squares to locally project
points to potential features. The
algorithm processes these points to
construct arc-length parameterized
spline curves fit using an iterative
refinement method, aligning smooth
and continuous curves through the
feature points. We demonstrate the
benefits of our method with three
applications: surface segmentation,
surface meshing and point-based
compression.
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