Scalable visualization of time-varying multi-parameter distributions using spatially organized histograms

Tyson Neuroth, Franz Sauer, Weixing Wang, Stephane Ethier, Choong Seock Chang, Kwan-Liu Ma

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Visualizing distributions from data samples as well as spatial and temporal trends of multiple variables is fundamental to analyzing the output of today's scientific simulations. However, traditional visualization techniques are often subject to a trade-off between visual clutter and loss of detail, especially in a large-scale setting. In this work, we extend the use of spatially organized histograms into a sophisticated visualization system that can more effectively study trends between multiple variables throughout a spatial domain. Furthermore, we exploit the use of isosurfaces to visualize time-varying trends found within histogram distributions. This technique is adapted into both an on-the-fly scheme as well as an in situ scheme to maintain real-time interactivity at a variety of data scales.

Original languageEnglish (US)
Article number7792155
Pages (from-to)2599-2612
Number of pages14
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number12
StatePublished - Dec 1 2017


  • Histograms
  • In situ processing
  • Isosurfaces
  • Large-scale data
  • Particle data
  • Scientific visualization
  • Time-varying data

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design


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