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Comparing Cross-Sections and 3D Renderings for Surface Matching Tasks using Physical Ground Truths

Andreas Johnsen Lind, Stefan Bruckner

ARTICLE, IEEE Transactions on Visualization and Computer Graphics, jan, 2017

Abstract

Within the visualization community there are some well-known techniques for visualizing 3D spatial data and some general assumptions about how perception affects the performance of these techniques in practice. However, there is a lack of empirical research backing up the possible performance differences among the basic techniques for general tasks. One such assumption is that 3D renderings are better for obtaining an overview, whereas cross sectional visualizations such as the commonly used Multi- Planar Reformation (MPR) are better for supporting detailed analysis tasks. In the present study we investigated this common assumption by examining the difference in performance between MPR and 3D rendering for correctly identifying a known surface. We also examined whether prior experience working with image data affects the participantís performance, and whether there was any difference between interactive or static versions of the visualizations. Answering this question is important because it can be used as part of a scientific and empirical basis for determining when to use which of the two techniques. An advantage of the present study compared to other studies is that several factors were taken into account to compare the two techniques. The problem was examined through an experiment with 45 participants, where physical objects were used as the known surface (ground truth). Our findings showed that: 1. The 3D renderings largely outperformed the cross sections; 2. Interactive visualizations were partially more effective than static visualizations; and 3. The high experience group did not generally outperform the low experience group.

Published

IEEE Transactions on Visualization and Computer Graphics

  • Volume: 23
  • Number: 1
  • Event: IEEE SciVis 2016
  • Location: Baltimore, USA
  • Date: jan 2017

Media

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BibTeX

@ARTICLE{Lind-2017-CCR,
  author = {Andreas Johnsen Lind and Stefan Bruckner},
  title = {Comparing Cross-Sections and 3D Renderings for Surface Matching Tasks
	using Physical Ground Truths},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  year = {2017},
  volume = {23},
  number = {1},
  month = jan,
  note = {Accepted for publication, to be presented at IEEE SciVis 2016},
  abstract = {Within the visualization community there are some well-known techniques
	for visualizing 3D spatial data and some general assumptions about
	how perception affects the performance of these techniques in practice.
	However, there is a lack of empirical research backing up the possible
	performance differences among the basic techniques for general tasks.
	One such assumption is that 3D renderings are better for obtaining
	an overview, whereas cross sectional visualizations such as the commonly
	used Multi- Planar Reformation (MPR) are better for supporting detailed
	analysis tasks. In the present study we investigated this common
	assumption by examining the difference in performance between MPR
	and 3D rendering for correctly identifying a known surface. We also
	examined whether prior experience working with image data affects
	the participantís performance, and whether there was any difference
	between interactive or static versions of the visualizations. Answering
	this question is important because it can be used as part of a scientific
	and empirical basis for determining when to use which of the two
	techniques. An advantage of the present study compared to other studies
	is that several factors were taken into account to compare the two
	techniques. The problem was examined through an experiment with 45
	participants, where physical objects were used as the known surface
	(ground truth). Our findings showed that: 1. The 3D renderings largely
	outperformed the cross sections; 2. Interactive visualizations were
	partially more effective than static visualizations; and 3. The high
	experience group did not generally outperform the low experience
	group.},
  event = {IEEE SciVis 2016},
  doi = {10.1109/TVCG.2016.2598602},   

  keywords = {human-computer interaction, quantitative evaluation, volume visualization},
  location = {Baltimore, USA},

}






 Last Modified: Jean-Paul Balabanian, 2017-10-28