 | GigaVoxels: Voxels Come Into Play Crassin, Cyril Crytek Conference Talk. Crytek GmbH. Frankfurt, Germany, 2009. (Misc) (Links | BibTeX | Tags: gpu, voxels, ray-tracing, GigaVoxels, cache) @misc{Cra09,
name = {GigaVoxels: Voxels Come Into Play},
author = {Crassin, Cyril},
url = {http://artis.imag.fr/Publications/2009/Cra09, INRIA Webpage
http://maverick.inria.fr/Publications/2009/Cra09/GigaVoxels_Crytek_web.ppt, Talk PPT},
year = {2009},
date = {2009-11-01},
booktitle = {Crytek Conference Talk. Crytek GmbH. Frankfurt, Germany},
journal = {Crytek Conference Talk. Crytek GmbH. Frankfurt, Germany},
keywords = {gpu, voxels, ray-tracing, GigaVoxels, cache}
}
|
 | Building with Bricks: Cuda-based Gigavoxel Rendering Crassin, Cyril; Neyret, Fabrice; Eisemann, Elmar Intel Visual Computing Research Conference, 2009. (Inproceeding) (Abstract | Links | BibTeX | Tags: Voxel, out-of-core, filtering, voxelization, gpu, ray-tracing, depth-of-field, real-time rendering, ray-casting, octree, GigaVoxels, cache) @inproceedings{CNE09,
name = {Building with Bricks: Cuda-based Gigavoxel Rendering},
author = {Crassin, Cyril and Neyret, Fabrice and Eisemann, Elmar},
url = {http://artis.imag.fr/Publications/2009/CNE09, INRIA Webpage
/research/publications/CNE09/IntelConf_Final.pdf, Paper Authors Version},
year = {2009},
date = {2009-03-01},
booktitle = {Intel Visual Computing Research Conference},
journal = {Intel Visual Computing Research Conference},
abstract = {For a long time, triangles have been considered the state-of-sthe-art primitive for fast interactive applications.
Only recently, with the dawn of programmability of graphics cards, different representations emerged. Especially for complex entities, triangles have difficulties in representing convincing details and faithful approximations quickly become costly. In this work we investigate Voxels. Voxels can represent very rich and detailed objects and are of crucial importance in medical contexts. Nonetheless, one major downside is their significant memory consumption. Here, we propose an out-of-core method to deal with large volumes in real-time. Only little CPU interaction is needed which shifts the workload towards the GPU. This makes the use of large voxel data sets even easier than the, usually complicated, triangle-based LOD mechanisms that often rely on the CPU. This simplicity might even foreshadow the use of volume data, in game contexts. The latter we underline by presenting very efficient algorithms to approximate standard effects, such as soft shadows, or depth of field.},
keywords = {Voxel, out-of-core, filtering, voxelization, gpu, ray-tracing, depth-of-field, real-time rendering, ray-casting, octree, GigaVoxels, cache}
}
For a long time, triangles have been considered the state-of-sthe-art primitive for fast interactive applications.
Only recently, with the dawn of programmability of graphics cards, different representations emerged. Especially for complex entities, triangles have difficulties in representing convincing details and faithful approximations quickly become costly. In this work we investigate Voxels. Voxels can represent very rich and detailed objects and are of crucial importance in medical contexts. Nonetheless, one major downside is their significant memory consumption. Here, we propose an out-of-core method to deal with large volumes in real-time. Only little CPU interaction is needed which shifts the workload towards the GPU. This makes the use of large voxel data sets even easier than the, usually complicated, triangle-based LOD mechanisms that often rely on the CPU. This simplicity might even foreshadow the use of volume data, in game contexts. The latter we underline by presenting very efficient algorithms to approximate standard effects, such as soft shadows, or depth of field. |
