Surface approximation of 3D objects from irregularly sampled clouds of 3D points using spherical wavelets

This paper presents a technique for computing multiresolution shape models of 3D objects acquired as clouds of 3D points. The procedure is fully automated and is able to process data from any object with a genus equivalent to that of a sphere. An important feature of this method is that it does not impose any restrictions on the input data, which can be provided by any kind of 3D sensor. The method described here starts by computing an intermediate mesh that meets the subdivision connectivity requirement needed to allow the computation of the wavelet transform. The mesh is then adjusted to the 3D input data by means of an iterative deformation process. Finally, a spherical wavelet transform is computed to obtain the object's 3D multiresolution model The paper presents some real examples acquired with a hand-held 3D digitizer.