Efficient Sparse Voxel Octrees

• Published in: IEEE transactions on visualization and computer graphics Vol. 17; no. 8; pp. 1048 - 1059
• Main Authors: Laine, S, Karras, T
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.08.2011; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Approximation methods; Arrays; Casts; CUDA; Data structures; Filtering; Geometry; GPU; Graphics processing unit; Image color analysis; octree; Octrees; ray tracing; Rendering (computer graphics); Representations; Sampling; Shading; Storage; Studies; volumetric image representation; Voxel
• ISSN: 1077-2626; 1941-0506
• DOI: 10.1109/TVCG.2010.240

In this paper, we examine the possibilities of using voxel representations as a generic way for expressing complex and feature-rich geometry on current and future GPUs. We present in detail a compact data structure for storing voxels and an efficient algorithm for performing ray casts using this structure. We augment the voxel data with novel contour information that increases geometric resolution, allows more compact encoding of smooth surfaces, and accelerates ray casts. We also employ a novel normal compression format for storing high-precision object-space normals. Finally, we present a variable-radius postprocess filtering technique for smoothing out blockiness caused by discrete sampling of shading attributes. Based on benchmark results, we show that our voxel representation is competitive with triangle-based representations in terms of ray casting performance, while allowing tremendously greater geometric detail and unique shading information for every voxel. Our voxel codebase is open sourced and available at http://code.google.com/p/efficient-sparse-voxel-octrees/.