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Proceedings Paper

A multi-resolution interpolation scheme for pathline based Lagrangian flow representations
Author(s): Alexy Agranovsky; Harald Obermaier; Christoph Garth; Kenneth I. Joy
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Paper Abstract

Where the computation of particle trajectories in classic vector field representations includes computationally involved numerical integration, a Lagrangian representation in the form of a flow map opens up new alternative ways of trajectory extraction through interpolation. In our paper, we present a novel re-organization of the Lagrangian representation by sub-sampling a pre-computed set of trajectories into multiple levels of resolution, maintaining a bound over the amount of memory mapped by the file system. We exemplify the advantages of replacing integration with interpolation for particle trajectory calculation through a real-time, low memory cost, interactive exploration environment for the study of flow fields. Beginning with a base resolution, once an area of interest is located, additional trajectories from other levels of resolution are dynamically loaded, densely covering those regions of the flow field that are relevant for the extraction of the desired feature. We show that as more trajectories are loaded, the accuracy of the extracted features converges to the accuracy of the flow features extracted from numerical integration with the added benefit of real-time, non-iterative, multi-resolution path and time surface extraction.

Paper Details

Date Published: 8 February 2015
PDF: 12 pages
Proc. SPIE 9397, Visualization and Data Analysis 2015, 93970K (8 February 2015); doi: 10.1117/12.2083253
Show Author Affiliations
Alexy Agranovsky, Univ. of California, Davis (United States)
Harald Obermaier, Univ. of California, Davis (United States)
Christoph Garth, Technische Univ. Kaiserslautern (Germany)
Kenneth I. Joy, Univ. of California, Davis (United States)

Published in SPIE Proceedings Vol. 9397:
Visualization and Data Analysis 2015
David L. Kao; Ming C. Hao; Mark A. Livingston; Thomas Wischgoll, Editor(s)

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