Abstract:
Shallow k-d trees are an efficient empty space skipping data structure for sparse volume rendering and can be constructed in real-time for moderately sized data sets. Lar...Show MoreMetadata
Abstract:
Shallow k-d trees are an efficient empty space skipping data structure for sparse volume rendering and can be constructed in real-time for moderately sized data sets. Larger volume data sets however require deeper k-d trees that sufficiently cull empty space but take longer to construct. In contrast to k-d trees, uniform grids have inferior culling properties but can be constructed in real-time. We propose a hybrid data structure that employs hierarchical subdivision at the root level and a uniform grid at the leaf level to balance construction and rendering times for sparse volume rendering. We provide a thorough evaluation of this spatial index and compare it to state of the art space skipping data structures.
Published in: 2019 IEEE Visualization Conference (VIS)
Date of Conference: 20-25 October 2019
Date Added to IEEE Xplore: 19 December 2019
ISBN Information: