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<p><b>Abstract</b>—A novel approach to 3D part segmentation is presented. It is a well-known physical fact that electrical charge on the surface of a conductor tends to accumulate at a sharp convexity and vanish at a sharp concavity. Thus, object part boundaries, which are usually denoted by a sharp surface concavity, can be detected by simulating the electrical charge density over the object surface and locating surface points which exhibit local charge density minima. Beginning with single- or multi-view range data of a 3D object, we simulate the charge density distribution over an object's surface which has been tessellated by a triangular mesh. We detect the deep surface concavities by tracing local charge density minima and then decompose the object into parts at these points. The charge density computation does not require an assumption on surface smoothness and uses weighted global data to produce robust local surface features for part segmentation.</p>
Computer vision, 3D, range data, shape, part segmentation, physics-based vision, electrical charge density distribution, finite element, surface triangulation, surface characterization.

K. Wu and M. D. Levine, "3D Part Segmentation Using Simulated Electrical Charge Distributions," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 19, no. , pp. 1223-1235, 1997.
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