Visualization of particle traces in virtual environments

Kuester, Falko; Bruckschen, Ralph; Hamann, Bernd; Joy, Kenneth I.

doi:10.1145/505036.505038

Cited by 5 publications

(3 citation statements)

References 2 publications

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“…Here, there is also a 3D computer graphics rendering problem where the data to be rendered at each frame are simply too large to fit within graphics card memory. The techniques described here are similar to those described previously in the literature for solid domain (Lee and El-Tawil, 2008;Beneš and Kruis, 2015;Liangyin et al, 2018) and fluid domain (Kuester et al, 2001;Sobel et al, 2004;Falk et al, 2016;Zhao et al, 2017) data visualization, but we believe this research provides the first example of extending and using both styles of visualization simultaneously to display multiple instances of FSI data in a head-tracked, stereo VR environment. Thus, we provide a detailed account as a casestudy-level contribution.…”

Section: Sampling and Visualizing Solid Domain Datamentioning

confidence: 65%

Bento Box: An Interactive and Zoomable Small Multiples Technique for Visualizing 4D Simulation Ensembles in Virtual Reality

et al. 2019

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We present Bento Box, a virtual reality data visualization technique and bimanual 3D user interface for exploratory analysis of 4D data ensembles. Bento Box helps scientists and engineers make detailed comparative judgments about multiple time-varying data instances that make up a data ensemble (e.g., a group of 10 parameterized simulation runs). The approach is to present an organized set of complementary volume visualizations juxtaposed in a grid arrangement, where each column visualizes a single data instance and each row provides a new view of the volume from a different perspective and/or scale. A novel bimanual interface enables users to select a sub-volume of interest to create a new row on-the-fly, scrub through time, and quickly navigate through the resulting virtual "bento box." The technique is evaluated through a real-world case study, supporting a team of medical device engineers and computational scientists using in-silico testing (supercomputer simulations) to redesign cardiac leads. The engineers confirmed hypotheses and developed new insights using a Bento Box visualization. An evaluation of the technical performance demonstrates that the proposed combination of data sampling strategies and clipped volume rendering is successful in displaying a juxtaposed visualization of fluid-structure-interaction simulation data (39 GB of raw data) at interactive VR frame rates.

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Section: Sampling and Visualizing Solid Domain Datamentioning

confidence: 65%

Bento Box: An Interactive and Zoomable Small Multiples Technique for Visualizing 4D Simulation Ensembles in Virtual Reality

et al. 2019

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“…All these approaches have in common that they attempt to optimize the generation of a mesh-based isosurface representation, which can result in large numbers of triangles to be displayed. Bruckschen et al 11 and Kuester et al 12 used an out-of-core, point-based approach to interactively render time-varying vector field data in a virtual environment. Pascucci et al 13 re-ordered a voxel dataset based on a z-ordered space-filling curve, allowing them to extract arbitrary slices with increasing resolution from a previously re-ordered voxel dataset at interactive frame rates, using a homogeneous PC-cluster.…”

Section: Related Workmentioning

confidence: 99%

Interactive visualization of very large medical datasets using point-based rendering

Nuber

Bruckschen

Hamann

et al. 2003

Medical Imaging 2003: Visualization, Image-Guided Procedures, and Display

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Visualizing high-resolution volumetric medical datasets is a challenging task. Current off-the-shelf graphics hardware supports interactive texture-based volume-rendering of volumetric datasets up to a resolution of 512 3 data points only. We present a method that allows us to visualize higher-resolution datasets, providing images similar to texture-based volume-rendering techniques at interactive frame-rates and full resolution.Our approach is based on an out-of-core point-based rendering approach. We pre-process the data by grouping points in the given dataset according to their value on disk and read them, when needed, from disk to immediately stream data to the rendering hardware. The high resolution of the dataset and the density of the data points allows us to use a pure point-based rendering approach. The density of points with equal or similar values within the dataset can be considered as being high enough to display regions and contours using points only.With our data-stream based approach we achieve interactive frame-rates for volumes even exceeding 512 3 resolution. Interactivity is not restricted to navigation through the dataset itself. It is also possible to change the values of interest to be displayed in real-time, enabling us to change display-parameters and thus looking for interesting and important features and contours interactively. For a human brain extracted from a 753x1050x910 colored dataset we achieved frame-rates of 20 frames/second and more, depending on the values selected.We describe a new way to interactively display high-resolution datasets without any loss of detail. By using points instead of textured volumes we reduce the amount of data to be transferred to the graphics hardware when compared to hardware-supported texture-based volume rendering. Using a data-organization optimized for reading from disk, we reduce the number of disk-seeks, and thus the overall update-time for a change of parameter-values.

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“…Application of the VR for the particle method was reported in [5,6]. An interesting point of the timeline method is that it can be regarded as a visualization of the so-called frozen-in vector fields in fluid dynamics or in magnetohydrodynamics (MHD).…”

Section: Introductionmentioning

confidence: 99%

Virtual Reality Visualization of Frozen-in Vector Fields

Murata

Kageyama

2011

Plasma and Fusion Research

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Magnetic field lines in ideal magnetohydrodynamics (MHD) are frozen into the fluid. Three-dimensional (3-D) visualization of the frozen-in magnetic field lines are useful for MHD dynamo study since it extracts stretching, twisting, and folding components of the flow. A 3-D, interactive, and immersive visualization method for the frozen-in field lines based on the virtual reality (VR) technology is proposed. A VR system with the head and hand tracking functions provides an ideal environment for the frozen-in line visualization since the seeding of the initial 3-D curve and stereoscopic observation of its motion are naturally realized in the VR space.

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Visualization of particle traces in virtual environments

Cited by 5 publications

References 2 publications

Bento Box: An Interactive and Zoomable Small Multiples Technique for Visualizing 4D Simulation Ensembles in Virtual Reality

Bento Box: An Interactive and Zoomable Small Multiples Technique for Visualizing 4D Simulation Ensembles in Virtual Reality

Interactive visualization of very large medical datasets using point-based rendering

Virtual Reality Visualization of Frozen-in Vector Fields

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