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Visualization Symposium, IEEE Pacific (2011)
Hong Kong, China
Mar. 1, 2011 to Mar. 4, 2011
ISBN: 978-1-61284-935-5
pp: 171-178
In this paper, we discuss the extension and integration of the statistical concept of Kernel Density Estimation (KDE) in a scatterplot-like visualization for dynamic data at interactive rates. We present a line kernel for representing streaming data, we discuss how the concept of KDE can be adapted to enable a continuous representation of the distribution of a dependent variable of a 2D domain. We propose to automatically adapt the kernel bandwith of KDE to the viewport settings, in an interactive visualization environment that allows zooming and panning. We also present a GPU-based realization of KDE that leads to interactive frame rates, even for comparably large datasets. Finally, we demonstrate the usefulness of our approach in the context of three application scenarios - one studying streaming ship traffic data, another one from the oil & gas domain, where process data from the operation of an oil rig is streaming in to an on-shore operational center, and a third one studying commercial air traffic in the US spanning 1987 to 2008.
interactive systems, cartography, data visualisation, GPU-based realization, interactive visualization, streaming data, kernel density estimation, scatterplot-like visualization, zooming, panning, Kernel, Data visualization, Bandwidth, Estimation, Histograms, Marine vehicles, Pixel, G.3 [Mathematics of Computing]: Probability and Statistics—Time series analysis, I.3.3 [Computing Methodologies]: Computer Graphics—Picture/Image Generation
"Interactive visualization of streaming data with Kernel Density Estimation", Visualization Symposium, IEEE Pacific, vol. 00, no. , pp. 171-178, 2011, doi:10.1109/PACIFICVIS.2011.5742387
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