Icare3D

@inbook{CG12,
name = {Octree-Based Sparse Voxelization Using The GPU Hardware Rasterizer},
author = {Crassin, Cyril and Green, Simon},
url = {http://www.seas.upenn.edu/~pcozzi/OpenGLInsights/OpenGLInsights-SparseVoxelization.pdf, Chapter PDF
http://blog.icare3d.org/2012/05/gtc-2012-talk-octree-based-sparse.html, GTC 2012 Talk
http://www.gputechconf.com/gtcnew/on-demand-gtc.php?sessionTopic=&searchByKeyword=&submit=&select=+&sessionEvent=&sessionYear=&sessionFormat=#1465, GTC 2012 Talk Video
http://www.icare3d.org/research/GTC2012_Voxelization_public.pdf, GTC 2012 Slides PDF
http://www.icare3d.org/research/GTC2012_Voxelization_public.pptx, GTC 2012 Slides PPTX
http://openglinsights.com/, OpenGL Insights Website},
year = {2012},
date = {2012-07-01},
booktitle = {OpenGL Insights},
publisher = {CRC Press, Patrick Cozzi and Christophe Riccio},
abstract = {Discrete voxel representations are generating growing interest in a wide range of applications in computational sciences and particularly in computer graphics. In this chapter, we first describe an efficient OpenGL implementation of a simple surface voxelization algorithm that produces a regular 3D texture. This technique uses the GPU hardware rasterizer and the new image load/store interface exposed by OpenGL 4.2.

The first part of this chapter will allow to familiarize the reader with the general algorithm and the new OpenGL features we leverage. In the second part we describe an extension of this approach, which enables building and updating a sparse voxel representation in the form of an octree structure. In order to scale to very large scenes, our approach avoids relying on an intermediate full regular grid to build the structure and constructs the octree directly. This second approach exploits the draw indirect features standardized in OpenGL 4.0 in order to allow synchronization-free launching of shader threads during the octree construction, as well as the new atomic counter functions exposed in OpenGL 4.2.},
keywords = {Voxel, voxelization, gpu}
}

@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}
}