Shi Qingmin, JaJa Joseph
Institute for Advanced Computer Studies, Department of Electrical and Computer Engineering, University of Maryland, College Park, USA.
IEEE Trans Vis Comput Graph. 2006 Sep-Oct;12(5):1283-90. doi: 10.1109/TVCG.2006.157.
We propose a novel Persistent OcTree (POT) indexing structure for accelerating isosurface extraction and spatial filtering from volumetric data. This data structure efficiently handles a wide range of visualization problems such as the generation of view-dependent isosurfaces, ray tracing, and isocontour slicing for high dimensional data. POT can be viewed as a hybrid data structure between the interval tree and the Branch-On-Need Octree (BONO) in the sense that it achieves the asymptotic bound of the interval tree for identifying the active cells corresponding to an isosurface and is more efficient than BONO for handling spatial queries. We encode a compact octree for each isovalue. Each such octree contains only the corresponding active cells, in such a way that the combined structure has linear space. The inherent hierarchical structure associated with the active cells enables very fast filtering of the active cells based on spatial constraints. We demonstrate the effectiveness of our approach by performing view-dependent isosurfacing on a wide variety of volumetric data sets and 4D isocontour slicing on the time-varying Richtmyer-Meshkov instability dataset.
我们提出了一种新颖的持久八叉树（POT）索引结构，用于加速从体数据中提取等值面和进行空间滤波。这种数据结构能有效地处理各种可视化问题，例如生成视图相关的等值面、光线追踪以及对高维数据进行等值线切片。POT可以被视为区间树和按需分支八叉树（BONO）之间的混合数据结构，因为它在识别与等值面相对应的活跃单元方面达到了区间树的渐近边界，并且在处理空间查询时比BONO更高效。我们为每个等值值编码一个紧凑的八叉树。每个这样的八叉树仅包含相应的活跃单元，使得组合结构具有线性空间。与活跃单元相关的固有层次结构能够基于空间约束非常快速地过滤活跃单元。我们通过对各种体数据集执行视图相关的等值面绘制以及对时变的瑞利 - 迈尔科夫不稳定性数据集进行4D等值线切片，证明了我们方法的有效性。
