In this paper we propose a new approach for 3D object modeling and reconstruction from range data. Our approach is based on the modelization of the object surfaces with a new set of Radial Basis Functions, we call Parametric Radial Basis Functions PRBF. First, a set of Radial Basis Functions is fitted to a set of 3D scanned points in order to reconstruct the object geometry. Our originality is the fact that the reconstruction is independent from the object geometry and the number; it can be applied for smooth objects as well as objects with sharp boundaries. To enhance the efficiency of the RBF modelization, we propose also an efficient isosurface extraction method based on volumetric processing. Unlike conventional reconstruction techniques, no prior information about the acquisition process is required. We demonstrate the efficiency of our approach through a set of experiments.
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