In this thesis we analyze and compare two different methods for approximating the Gauss and mean curvature on a surface, which is given as a set of points. It is important to find a method that agrees well with the analytic Gauss and mean curvatures and guarantees robust estimations. There is a great interest in Gauss and mean curvature since these two curvatures give information about the local geometry of the surface around the point at which these curvatures are calculated.
The thesis begins with a short overview of differential theory and then the methods are explained and described. The reason for this is to give the reader an understanding of the theory before explaining the methods.
The first method is called Bézier surfaces, which interpolates the given points. These surfaces are differentiable which makes it possible to approximate the Gauss and mean curvature, and are therefore very well suited for our problem.
The second method comes from the research article ``Discrete Differential-Geometry Operators for Triangulated 2-Manifolds'' by Mark Meyer, Mathieu Desbrun, Peter Schröder and Alan H. Barr. Their algorithm requires a triangulated surface, which itself is a hard problem to solve (at least if one has requirements on the triangulation). Their approximations of the Gauss and mean curvatures use a well chosen area around the point, and the Gauss curvature also makes use of the Gauss-Bonnet theorem.
My simulations show that Bézier surfaces approximate both Gauss and mean curvature well, and the approximations seem to converge to the analytic value when the information gets better. The articles algorithm also works well for approximating both curvatures, though this method seems to depend somewhat on the triangulation. This gives some requirements on the triangulation and will therefore be a harder problem to solve. The approximations do not converge when given a triangulation with obtuse triangles, though it shows signs to do so.