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Graxels: Information Rich Primitives for the Visualization of Time-Dependent Spatial Data

Sergej Stoppel, Erlend Hodneland, Helwig Hauser, Stefan Bruckner

CONFERENCE PAPER: In Proceedings of VCBM 2016, pp. 183–192, 2016. DOI: 10.2312/vcbm.20161286

Abstract

Time-dependent volumetric data has important applications in areas as diverse as medicine, climatology, and engineering. However, the simultaneous quantitative assessment of spatial and temporal features is very challenging. Common visualization techniques show either the whole volume in one time step (for example using direct volume rendering) or let the user select a region of interest (ROI) for which a collection of time-intensity curves is shown. In this paper, we propose a novel approach that dynamically embeds quantitative detail views in a spatial layout. Inspired by the concept of small multiples, we introduce a new primitive graxel (graph pixel). Graxels are view dependent primitives of time-intensity graphs, generated on-the-fly by aggregating per-ray information over time and image regions. Our method enables the detailed feature-aligned visual analysis of time-dependent volume data and allows interactive refinement and filtering. Temporal behaviors like frequency relations, aperiodic or periodic oscillations and their spatial context are easily perceived with our method. We demonstrate the power of our approach using examples from medicine and the natural sciences.

Published

Proceedings of VCBM 2016

  • Pages: 183–192
  • Event: VCBM 2016
  • Location: Bergen, Norway
  • Date: September 2016
  • DOI: 10.2312/vcbm.20161286

Documents and Links

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BibTeX

@INPROCEEDINGS{Stoppel-2016-GIR,
  author = {Sergej Stoppel and Erlend Hodneland and Helwig Hauser and Stefan
	Bruckner},
  title = {Graxels: Information Rich Primitives for the Visualization of Time-Dependent
	Spatial Data},
  booktitle = {Proceedings of VCBM 2016},
  year = {2016},
  pages = {183--192},
  month = sep,
  abstract = {Time-dependent volumetric data has important applications in areas
	as diverse as medicine, climatology, and engineering. However, the
	simultaneous quantitative assessment of spatial and temporal features
	is very challenging. Common visualization techniques show either
	the whole volume in one time step (for example using direct volume
	rendering) or let the user select a region of interest (ROI) for
	which a collection of time-intensity curves is shown. In this paper,
	we propose a novel approach that dynamically embeds quantitative
	detail views in a spatial layout. Inspired by the concept of small
	multiples, we introduce a new primitive graxel (graph pixel). Graxels
	are view dependent primitives of time-intensity graphs, generated
	on-the-fly by aggregating per-ray information over time and image
	regions. Our method enables the detailed feature-aligned visual analysis
	of time-dependent volume data and allows interactive refinement and
	filtering. Temporal behaviors like frequency relations, aperiodic
	or periodic oscillations and their spatial context are easily perceived
	with our method. We demonstrate the power of our approach using examples
	from medicine and the natural sciences.},
  doi = {10.2312/vcbm.20161286},
  event = {VCBM 2016},
  keywords = {time-dependent data, volume data, small multiples},
  location = {Bergen, Norway},
}






 Last Modified: Stefan Bruckner, 2017-08-23