Automatic 3-D model synthesis from measured range data

In this paper, we propose an algorithm to construct 3-D surface model from a set of range data, based on non-uniform rational B-splines (NURBS) surfac e-fitting technique. It is assumed that the range data is initially unorgan ized and scattered 3-D points, while their connectivity is also unknown. Th e proposed algorithm consists of three stages: initial model approximation employing K-means clustering, hierarchical decomposition of the initial mod el, and construction of NURBS surface patch network. The initial model is a pproximated by both polyhedral and triangular model. Then, the initial mode l is represented by a hierarchical graph, which is efficiently used to cons truct the G(1) continuous NURBS patch network of the whole object, Experime nts are carried out on synthetic and real range data to evaluate the perfor mance of the proposed algorithm. It is shown that the initial model as well as the NURBS patch network are constructed automatically with tolerable co mputation. The modeling error of the NURBS model is reduced to 10%, compare d with the initial mesh model.