Wind tunnel data fusion and immersive visualization: a case study

Brewster,; Lazos,; Keefe,

doi:10.1109/visual.2001.964563

Cited by 5 publications

(1 citation statement)

References 7 publications

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“…Boring and Pang, 16 Johannsen and Moorhead, 17 and Kao 18 map velocity direction of a flow-field to a colormap. Different definitions or implementations of data fusion in scientific visualization can also be found in 19,20 . However, our contribution to this approach is a series of colormaps that reveal more subtle features than the ones used previously.…”

Section: Related Workmentioning

confidence: 99%

Multivariate Visualization with Data Fusion

Wong

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Kao

et al. 2002

Information Visualization

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We discuss a fusion-based visualization method to analyze a multivariate climate dataset and its metadata. The primary difference between a conventional visualization and a fusion-based visualization is that the former draws on a single image whereas the latter draws on multiple see-through layers, which are then overlaid on each other to form the final visualization. We propose optimized colormaps to highlight subtle features that would not be shown with conventional colormaps. We present fusion techniques that integrate multiple single-purpose visualization techniques into the same viewing space. Our highly flexible fusion approach allows scientists to explore multiple parameters concurrently by mixing and matching images without frequently reconstructing new visualizations from the data for every possible combination. Although our primary visualization application is climate modeling, we show with examples that our fundamental design -fusing layers of data images for multivariate visualization -can be generalized for other information visualization applications.

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