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

Autor:	Johnson S; Interactive Visualization Lab, Department of Computer Science, University of Minnesota, Minneapolis, MN, United States., Orban D; Interactive Visualization Lab, Department of Computer Science, University of Minnesota, Minneapolis, MN, United States., Runesha HB; Research Computing Center, University of Chicago, Chicago, IL, United States., Meng L; Research Computing Center, University of Chicago, Chicago, IL, United States., Juhnke B; Department of Mechanical Engineering, Earl E. Bakken Medical Devices Center, University of Minnesota, Minneapolis, MN, United States., Erdman A; Department of Mechanical Engineering, Earl E. Bakken Medical Devices Center, University of Minnesota, Minneapolis, MN, United States., Samsel F; Texas Advanced Computing Center, University of Texas, Austin, TX, United States., Keefe DF; Interactive Visualization Lab, Department of Computer Science, University of Minnesota, Minneapolis, MN, United States.
Jazyk:	angličtina
Zdroj:	Frontiers in robotics and AI [Front Robot AI] 2019 Jul 23; Vol. 6, pp. 61. Date of Electronic Publication: 2019 Jul 23 (Print Publication: 2019).
DOI:	10.3389/frobt.2019.00061
Abstrakt:	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. (Copyright © 2019 Johnson, Orban, Runesha, Meng, Juhnke, Erdman, Samsel and Keefe.)
Databáze:	MEDLINE
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