Recovery of Curvature and Torsion Features from Free-form 3D Meshes at Multiple Scales

A novel technique for multi-scale curvature computation on a smoothed 3-D surface is presented. This is achieved by convolving local parametrisations of the surface with 2-D Gaussian filters iteratively. In our technique, semigeodesic coordinates are constructed at each vertex of the mesh which becomes the local origin. A geodesic from the origin is first constructed in an arbitrary direction such as the direction of one of the incident edges. The smoothing eliminates surface noise and small surface detail gradually, and results in gradual simplification of the object shape. The surface Gaussian and mean curvature values are estimated accurately at multiple scales together with curvature zero-crossing contours. The curvature values are then mapped to colours/grey-scales and displayed directly on the surface. Furthermore, local maxima of Gaussian and mean curvatures as well as the torsion maxima of the zero-crossing contours of Gaussian and mean curvatures were also located and displayed on the surface. These features can be utilised by later processes for robust surface matching and object recognition. Our technique is independent of the underlying triangulation and is also more efficient than volumetric diffusion techniques since 2-D rather than 3-D convolutions are employed. Another advantage is that it is applicable to incomplete surfaces which arise during occlusion or surfaces with holes.