Constructing NURBS surface model from scattered and unorganized range data

We propose an algorithm to produce a 3D surface model from a set of range data, based on the Non-Uniform Rational B-Splines (NURBS) surface fitting technique. It is assumed that the range data is initially unorganized and scattered 3D points, while their connectivity is also unknown. The proposed algorithm is roughly made up of two stages: initial model approximation employing K-means clustering, and construction of NURBS patch network using hierarchical graph representation. The initial model is approximated by both a polyhedral and triangular model. Then, the initial model is represented by a hierarchical graph, which is efficiently used to construct the G/sup 1/ continuous NURBS patch network of the whole object. Experiments are carried out on synthetic and real range data to evaluate the performance of the proposed algorithm. It is shown that the initial model, as well as the NURBS patch network, are constructed automatically, while the modeling error is observed to be negligible.