Isosurface Extraction and Spatial Filtering using Persistent Octree (POT)

TitleIsosurface Extraction and Spatial Filtering using Persistent Octree (POT)
Publication TypeJournal Articles
Year of Publication2006
AuthorsShi Q, JaJa JF
JournalVisualization and Computer Graphics, IEEE Transactions on
Pagination1283 - 1290
Date Published2006/10//sept
ISBN Number1077-2626
Keywords4D isocontour slicing;Richtmyer-Meshkov instability dataset;branch-on-need octree;hybrid data structure;isosurface extraction;persistent octree;spatial filtering;data visualisation;database indexing;feature extraction;octrees;spatial data structures;Algor, Computer-Assisted;Imaging, Three-Dimensional;Information Storage and Retrieval;User-Computer Interface;

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