Efficient multi-scale curvature and crease estimation

We consider the problem of multi-scale estimation of principal curvatures and crease lines on a surface represented with a mesh of triangles and affected by noise. We show that curvature at different scales can be efficiently and accurately estimated by modifying a fitting technique and applying it to neighborhoods of various size, depending on scale: we discard bending portions of surfaces during fitting, and we apply Monte-Carlo sampling to speed up computation. Next we propose a new technique for extracting crease lines and we show how such lines can summarize shape features at the various scales. This is a first step towards building a scale-space of surface features.