We describe an effective and novel approach to infer sign and direction of principal curvatures at each input site from noisy 3D data. Unlike most previous approaches, no local surface fitting, partial derivative computation of any kind, nor oriented normal vector recovery is performed in our method. These approaches are noise-sensitive since accurate, local, partial derivative information is o...