Visualization Symposium, IEEE Pacific (2011)
Hong Kong, China
Mar. 1, 2011 to Mar. 4, 2011
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