dc.contributor.author | Lampe, Ove Daae | eng |
dc.contributor.author | Hauser, Helwig | eng |
dc.date.accessioned | 2011-12-15T09:48:00Z | |
dc.date.available | 2011-12-15T09:48:00Z | |
dc.date.issued | 2011 | eng |
dc.identifier.isbn | 978-1-61284-935-5 | en_US |
dc.identifier.uri | https://hdl.handle.net/1956/5296 | |
dc.description | Presented at: Pacific Visualization Symposium, 1-4 March 2011, Hong Kong, China | en |
dc.description.abstract | In this paper, we discuss the extension and integration of the statistical concept of Kernel Density Estimation (KDE) in a scatterplotlike 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. | en_US |
dc.language.iso | eng | eng |
dc.publisher | IEEE | en_US |
dc.relation.ispartof | <a href="http://hdl.handle.net/1956/5302" target="blank">Interactive Visual Analysis of Process Data</a> | en_US |
dc.relation.ispartof | Proceedings of the IEEE Pacific Visualization Symposium 2011 | |
dc.title | Interactive Visualization of Streaming Data with Kernel Density Estimation | en_US |
dc.type | Chapter | |
dc.type | Peer reviewed | |
dc.description.version | acceptedVersion | en_US |
dc.rights.holder | Copyright IEEE | en_US |
dc.identifier.doi | https://doi.org/10.1109/pacificvis.2011.5742387 | |
dc.identifier.cristin | 881604 | |
dc.subject.nsi | VDP::Mathematics and natural science: 400::Information and communication science: 420::Simulation, visualization, signal processing, image processing: 429 | en_US |
dc.identifier.citation | In: Pacific Visualization Symposium (PacificVis), 2011 IEEE, pp 171 - 178 | |