Efficient High-Quality Volume Rendering of SPH Data

September 27th, 2010

Efficient High-Quality Volume Rendering of SPH DataAbstract:

High quality volume rendering of SPH data requires a complex order-dependent resampling of particle quantities along the view rays. In this paper we present an efficient approach to perform this task using a novel view-space discretization of the simulation domain. Our method draws upon recent work on GPU-based particle voxelization for the efficient resampling of particles into uniform grids. We propose a new technique that leverages a perspective grid to adaptively discretize the view-volume, giving rise to a continuous level-of-detail sampling structure and reducing memory requirements compared to a uniform grid. In combination with a level-of-detail representation of the particle set, the perspective grid allows effectively reducing the amount of primitives to be processed at run-time. We demonstrate the quality and performance of our method for the rendering of fluid and gas dynamics SPH simulations consisting of many millions of particles.

(Roland Fraedrich, Stefan Auer, and Rüdiger Westermann: “Efficient High-Quality Volume Rendering of SPH Data”, IEEE Transactions on Visualization and Computer Graphics (Proceedings of IEEE Visualization 2010), vol. 16, no. 6, Nov.-Dec. 2010, Link to project webpage including paper, pictures and video)

  • Stefan

    It is probably interesting for special VR effects but it totally ignores the most practically important application to visualize CT data sets. VR of CT data sets is the most practically relevant and demanded applications, therefore the most competitive and advanced. It is difficult to judge how good proposed VR technique is comparatively already available on the market VR solutions once the rendering results/specs for CT data is not shown.

  • Stefan

    The focus of this paper is visualization of particle data, not CT volume data. If you’re interested in volume rendering for medical application, perhaps you find something here: http://wwwcg.in.tum.de/Research/Projects/SciVis

    • Stefan

      >The focus of this paper is visualization of particle data, not CT volume data

      They re-sample adaptively into uniform grids and it is a perfect fit to do an adaptive VR rendering for CT data as well; essentially any adaptive VR technique is doomed to do something like this.


      I could not find any testable substance there – just words; please point to the binaries I may run VR to validate how good presented VR techniques are. It is rather a rhetorical request, there is nothing there… please prove me wrong. Once it has no monetary potential it goes to public domain (besides a very rare exceptions).