Multiple representation approach to geometric model construction from range data

This paper concentrates on techniques for constructing geometric models from data provided by 3-D imaging sensors. Such techniques allow for rapid modeling of sculptured free-form shapes and generation of geometric models for existing parts. Also, the problem of merging images in order to obtain a complete 3-D data set is addressed. The shape representations are closely related to modeling primitives commonly used in computer aided geometric design. In particular, Non-Uniform Rational B-Spline (NURBS), optimal triangulation and superellipsoid surface representations are used in the shape estimation. Computational solutions are provided for shape estimation. The surface approximations are refined by the algorithms to meet a user defined tolerance value. The resulting geometric model is in a procedural form which can convey structural information in addition to low level geometric primitives. Experimental results on view registration and shape estimation are shown