Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Using particles to sample and control implicit surfaces
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Isosurface extraction using particle systems
VIS '97 Proceedings of the 8th conference on Visualization '97
Reducing aliasing artifacts in iso-surfaces of binary volumes
VVS '00 Proceedings of the 2000 IEEE symposium on Volume visualization
Tight cocone: a water-tight surface reconstructor
SM '03 Proceedings of the eighth ACM symposium on Solid modeling and applications
UberFlow: a GPU-based particle engine
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Hardware-based simulation and collision detection for large particle systems
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
A Particle System for Interactive Visualization of 3D Flows
IEEE Transactions on Visualization and Computer Graphics
Robust Particle Systems for Curvature Dependent Sampling of Implicit Surfaces
SMI '05 Proceedings of the International Conference on Shape Modeling and Applications 2005
Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles
IEEE Transactions on Visualization and Computer Graphics
Particle-based Sampling and Meshing of Surfaces in Multimaterial Volumes
IEEE Transactions on Visualization and Computer Graphics
Interactive SPH simulation and rendering on the GPU
Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
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Extracting isosurfaces represented as high quality meshes from three-dimensional scalar fields is needed for many important applications, particularly visualization and numerical simulations. One recent advance for extracting high quality meshes for isosurface computation is based on a dynamic particle system. Unfortunately, this state-of-the-art particle placement technique requires a significant amount of time to produce a satisfactory mesh. To address this issue, we study the parallelism property of the particle placement and make use of CUDA, a parallel programming technique on the GPU, to significantly improve the performance of particle placement. This paper describes the curvature dependent sampling method used to extract high quality meshes and describes its implementation using CUDA on the GPU.