A procedure for 3D model construction from sparsely and irregularly sampled points is presented. A two-stage dynamic deformation process is presented which is designed to produce desirable mesh properties despite difficult data characteristics. In a first phase, a mesh of springs is snapped down to the convex hull of the data. In the second phase, a pseudo-gravity model is used to attract the mesh points into concave surface patches. This modeling technique is a new contribution to dynamic modeling methods. This process reduces the undesirable effects of oversmoothness, local concentration, and folding that result from the sparsity and randomness of sampled data. Our experiments show that the proposed deformation process preserves to some extent both the shape and size uniformities of the patches constituting models. Furthermore, our modeling process fits surfaces with prominent concavities without prior segmentation of input data.
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