Efficient Extraction of Geometric Information from Point Cloud Data

A kernel-based method is proposed to construct signature (defining) functions of subsets of Rd, ranging from full dimensional manifolds to point clouds. The signature function can be used to estimate the dimension, normal, and curvatures of the interpolated surface, without requiring explicit knowledge of local neighborhoods or other data structure.