Modeling surfaces of arbitrary topology with dynamic particles

A new approach to surface modeling and reconstruction is developed which overcomes some important limitations of existing surface representations methods. The approach features two components. The first is a dynamic self-organizing oriented particle system which discovers topological and geometric surface structure implicit in visual data. The oriented particles evolve according to Newtonian mechanics and interact through long-range attraction forces, short-range repulsion forces, and coplanarity, conormality, and cocircularity forces. The second component is an efficient triangulation scheme that connects the particles into a continuous global surface model that is consistent with the inferred structure. A flexible surface reconstruction algorithm is developed that can compute complete, detailed, viewpoint-invariant geometric surface descriptions of objects with arbitrary topology. The algorithms are applied to 3-D medical image segmentation and to surface reconstruction from object silhouettes.<
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