Dynamic Particle Systems for Adaptive Sampling of Implicit Surfaces

The generation of a set of point samples is a ubiquitous requirement in many mathematical and computational problems -- from shape statistics, to mesh generation, to visualization. Dynamic particle systems are an intuitive and controllable mechanism for producing very even distributions of points across complex implicit surfaces. Controlled by only a few constraints, these systems can robustly provide nearly-regular packings that smoothly adapt to surface features. The constraints cause particles to first stick to the zeroset of an implicit function, and then to move across the surface until particles are arranged in minimal energy configurations. Adaptivity is added into the system by scaling the distance between particles, causing higher densities of particles around surface features. The end result is an adaptive, yet very regular, set of surface points.

Related Papers:

	Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles accepted to IEEE Transactions on Visualization and Computer Graphics (Proceedings of Visualization 2007) Miriah Meyer, Robert M. Kirby, Ross Whitaker
	Particle Systems for Efficient and Accurate High-Order Finite Element Visualization IEEE Transactions on Visualization and Computer Graphics, Sept/Oct 2007 Miriah Meyer, Blake Nelson, Robert M. Kirby, Ross Whitaker
	Robust Particle Systems for Curvature Dependent Sampling of Implicit Surfaces International Conference on Shape Modeling and Applications (SMI), 2005 Miriah Meyer, Pierre Georgel, Ross Whitaker

All Publications