Adaptive extraction of time-varying isosurfaces

Gregorski, Benjamin F.; Senecal, Joshua G.; Duchaineau, Mark A.; Joy, Kenneth I.

doi:10.1109/tvcg.2004.35

Cited by 17 publications

(13 citation statements)

References 33 publications

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“…An alternative approach is to directly encode the cluster of tetrahedra sharing a longest edge [2,8,9,26,28]. Gregorski et al [8] denote such a primitive as a diamond, and propose an implicit representation for the spatial and hierarchical relationships of a diamond based on its level, orientation and position.…”

Section: Related Workmentioning

confidence: 99%

“…There have been many proposed optimizations to enable interactive visualization of LEB hierarchies including frame-to-frame coherence [3,8], parallel rendering [7], front-to-back sorting, viewdependent rendering [16], tetrahedral stripping [20], and chunked updates [9,1]. Since our model is based on the same hierarchies, these optimizations can be easily incorporated into our pipeline.…”

Section: Related Workmentioning

confidence: 99%

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Supercubes: A High-Level Primitive for Diamond Hierarchies

Weiss

Floriani

2009

IEEE Trans. Visual. Comput. Graphics

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Abstract-Volumetric datasets are often modeled using a multiresolution approach based on a nested decomposition of the domain into a polyhedral mesh. Nested tetrahedral meshes generated through the longest edge bisection rule are commonly used to decompose regular volumetric datasets since they produce highly adaptive crack-free representations. Efficient representations for such models have been achieved by clustering the set of tetrahedra sharing a common longest edge into a structure called a diamond. The alignment and orientation of the longest edge can be used to implicitly determine the geometry of a diamond and its relations to the other diamonds within the hierarchy. We introduce the supercube as a high-level primitive within such meshes that encompasses all unique types of diamonds. A supercube is a coherent set of edges corresponding to three consecutive levels of subdivision. Diamonds are uniquely characterized by the longest edge of the tetrahedra forming them and are clustered in supercubes through the association of the longest edge of a diamond with a unique edge in a supercube. Supercubes are thus a compact and highly efficient means of associating information with a subset of the vertices, edges and tetrahedra of the meshes generated through longest edge bisection. We demonstrate the effectiveness of the supercube representation when encoding multiresolution diamond hierarchies built on a subset of the points of a regular grid. We also show how supercubes can be used to efficiently extract meshes from diamond hierarchies and to reduce the storage requirements of such variable-resolution meshes.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Supercubes: A High-Level Primitive for Diamond Hierarchies

Weiss

Floriani

2009

IEEE Trans. Visual. Comput. Graphics

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“…All these out-of-core techniques are for steadystate datasets. As for time-varying fields, Sutton and Hansen [20], Gregorski et al [11] and Waters et al [22] developed out-of-core isosurface extraction methods for regular grids, and Chiang [3] developed an out-of-core isosurface approach for irregular grids. Also, Gao et al [9] employed the TSP tree scheme [17] for distributed parallel volume rendering that addresses some I/O issues such as data caching and prefetching, with the main focus on distributed data management in parallel computing.…”

Section: Previous Workmentioning

confidence: 99%

“…For example, in Fig. 2(b), the nodes of Z are ready in the following order: 1, 2, 9, 3, 4, 10, 13,5,6,11,7,8,12,14,15. When a node τ of Z is ready, we can compute the errors of Eqs.…”

Section: The Slice Accumulation Algorithmmentioning

confidence: 99%

Out-of-core volume rendering for time-varying fields using a space-partitioning time (SPT) tree

Chiang

Shen³

2009

2009 IEEE Pacific Visualization Symposium

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In this paper, we propose a novel out-of-core volume rendering algorithm for large time-varying fields. Exploring temporal and spatial coherences has been an important direction for speeding up the rendering of time-varying data. Previously, there were techniques that hierarchically partition both the time and space domains into a data structure so as to re-use some results from the previous time step in multiresolution rendering; however, it has not been studied on which domain should be partitioned first to obtain a better re-use rate. We address this open question, and show both theoretically and experimentally that partitioning the time domain first is better. We call the resulting structure (a binary time tree as the primary structure and an octree as the secondary structure) the spacepartitioning time (SPT) tree. Typically, our SPT-tree rendering has a higher level of details, a higher re-use rate, and runs faster. In addition, we devise a novel cut-finding algorithm to facilitate efficient out-of-core volume rendering using our SPT tree, we develop a novel out-of-core preprocessing algorithm to build our SPT tree I/O-efficiently, and we propose modified error metrics with a theoretical guarantee of a monotonicity property that is desirable for the tree search. The experiments on datasets as large as 25GB using a PC with only 2GB of RAM demonstrated the efficacy of our new approach.

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“…For time-varying fields, Shen [21] gave an in-core technique based on the THI tree. Out-of-core algorithms include the temporal branch-onneed octree method by Sutton and Hansen [26], the adaptive extraction approach by Gregorski et al [12], the time-tree algorithm by Chiang [5], and the difference intervals technique by Waters et al [29].…”

Section: Previous Workmentioning

confidence: 99%

Isosurface Extraction and View-Dependent Filtering from Time-Varying Fields Using Persistent Time-Octree (PTOT)

Chiang

2009

IEEE Trans. Visual. Comput. Graphics

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Abstract-We develop a new algorithm for isosurface extraction and view-dependent filtering from large time-varying fields, by using a novel Persistent Time-Octree (PTOT) indexing structure. Previously, the Persistent Octree (POT) was proposed to perform isosurface extraction and view-dependent filtering, which combines the advantages of the interval tree (for optimal searches of active cells) and of the Branch-On-Need Octree (BONO, for view-dependent filtering), but it only works for steady-state (i.e., single time step) data. For time-varying fields, a 4D version of POT, 4D-POT, was proposed for 4D isocontour slicing, where slicing on the time domain gives all active cells in the queried time step and isovalue. However, such slicing is not output sensitive and thus the searching is sub-optimal. Moreover, it was not known how to support view-dependent filtering in addition to time-domain slicing. In this paper, we develop a novel Persistent Time-Octree (PTOT) indexing structure, which has the advantages of POT and performs 4D isocontour slicing on the time domain with an output-sensitive and optimal searching. In addition, when we query the same isovalue q over m consecutive time steps, there is no additional searching overhead (except for reporting the additional active cells) compared to querying just the first time step. Such searching performance for finding active cells is asymptotically optimal, with asymptotically optimal space and preprocessing time as well. Moreover, our PTOT supports view-dependent filtering in addition to time-domain slicing. We propose a simple and effective out-of-core scheme, where we integrate our PTOT with implicit occluders, batched occlusion queries and batched CUDA computing tasks, so that we can greatly reduce the I/O cost as well as increase the amount of data being concurrently computed in GPU. This results in an efficient algorithm for isosurface extraction with viewdependent filtering utilizing a state-of-the-art programmable GPU for time-varying fields larger than main memory. Our experiments on datasets as large as 192GB (with 4GB per time step) having no more than 870MB of memory footprint in both preprocessing and run-time phases demonstrate the efficacy of our new technique.Index Terms-Isosurface extraction, time-varying fields, persistent data structure, view-dependent filtering, out-of-core methods.

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Adaptive extraction of time-varying isosurfaces

Cited by 17 publications

References 33 publications

Supercubes: A High-Level Primitive for Diamond Hierarchies

Supercubes: A High-Level Primitive for Diamond Hierarchies

Out-of-core volume rendering for time-varying fields using a space-partitioning time (SPT) tree

Isosurface Extraction and View-Dependent Filtering from Time-Varying Fields Using Persistent Time-Octree (PTOT)

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