The use of point sets instead ofmeshes becamemore popular during
the last years. We present a new method for anisotropic fairing of a
point sampled surface using an anisotropic geometric mean curvature
flow. The main advantage of our approach is that the evolution
removes noise from a point set while it detects and enhances geometric
features of the surface such as edges and corners. We derive
a shape operator, principal curvature properties of a point set, and
an anisotropic Laplacian of the surface. This anisotropic Laplacian
reflects curvature properties which can be understood as the point
set analogue of Taubin’s curvature-tensor for polyhedral surfaces.
We combine these discrete tools with techniques from geometric
diffusion and image processing. Several applications demonstrate
the efficiency and accuracy of our method.