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Interactive Visualization of Streaming Data with Kernel Density Estimation

Ove Daae Lampe, Helwig Hauser

INPROCEEDINGS, Proceedings of the IEEE Pacific Visualization Symposium (PacificVis 2011), March, 2011

Abstract

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 and 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.

Published

Proceedings of the IEEE Pacific Visualization Symposium (PacificVis 2011)

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BibTeX

@inproceedings{lampe11kde,
  title = {Interactive Visualization of Streaming Data with Kernel Density Estimation},
  author = {Ove Daae Lampe and Helwig Hauser},
  year = {2011},
  booktitle = {Proceedings of the IEEE Pacific Visualization Symposium (PacificVis 2011)},
  abstract = {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 and 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.},
  pages = {171--178},
  month = {March},
  location = {Hong Kong},


  URL = {http://dx.doi.org/10.1109/PACIFICVIS.2011.5742387},


}






 Last Modified: Jean-Paul Balabanian, 2014-04-09