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Interactive Focus+Context Visualization with Linked 2D/3D Scatterplots
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| Abstract:
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Scatterplots in 2D and 3D are very useful tools, but also
suffer from a number of problems. Overplotting hides the
true number of points that are displayed, and showing point
clouds in 3D is problematic both in terms of perception and
interaction.
We propose a combination of 2D and 3D scatterplots, together
with some extensions to overcome these problems. By
linking 2D and 3D views, it is possible to interact in 2D and
get feedback in 3D. That feedback is also enhanced by depth
cues (color and point size) such that the user gets a better
depth impression. Histograms in 2D and 3D show additional
information about point densities and additional context
can be displayed. An example application demonstrates
the usefulness of the technique.
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| Project:
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This work has been carried out as part of the
basic research project ``interactive visualization''
at the VRVis research center in Vienna, Austria,
which is funded by an Austrian governmental research
project called Kplus.
All data sets shown in the images on this page are courtesy of
AVL List GmbH, Graz, Austria.
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| Paper:
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The paper (12 pages)
is accepted for publication in the Proceedings of the 2nd International Conference on Coordinated & Multiple Views in Exploratory
Visualization (CMV 2004), July 13, 2004, London, United Kingdom.
The images on this web page are taken from this paper.
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| Video: |
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Short movie (approx. 2 minutes) demonstrating extensions, interaction and application of the linked 2D/3D Scatterplot.
small version (304 x 304 pixels, approx. 5.6MB)
large version (512 x 512 pixels, approx. 20MB)
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Results
(to retrieve an enlarged version
of the images, click on them)
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Figure 1: The combined 2D and 3D scatterplot with user interface.
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Figure 2: Improving depth perception. Left: No depth cues are used; Middle: Depth is indicated with point size and halos are used to
ease the discrimination of single points; Right: Depth cueing using both color and point size, as well as halos.
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Figure 3: Representing point density with transparent 2D histograms: The density is not clearly recognizable in the left third. In the middle, a texture-based
representation uses opacity only, while the right third illustrates mapping density to opacity as well as the height of axis-aligned bins.
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Figure 4: Representing spatial context: The perspective projection (left, drawn using projection-aligned transparent bars) captures the whole
spatial context, while the orthographic projection (right) omits parts of it (the lobe in the bottom right corner for example).
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Figure 5: Displaying temporal context as grey points.
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Figure 6:Composite smooth brushing in the combined 2D/3D View: Two cuboid-shaped basic brushes are logically OR-combined.
The brushes are drawn as rectangles in 2D and as transparent boxes in 3D.
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Figure 7:Extensions for 2D scatterplots: Histograms indicate the point density of the whole focus and the brushed focus and
grey areas represent temporal context.
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Figure 8: An InfoVis dataset: The attribute 'year' is mapped to color, the attributes 'weight', 'horsepower' and 'miles
per gallon' are mapped to the axes.
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Figure 9: The evolution of velocity, pressure and turbulence over time in the dataset of the case study (T-junction).
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Figure 10: Mapping brushed physical space to attribute space: The main chamber of the T-junction
(shown in the linked 3D View of SimVis) closely corresponds to the lobe at high pressure in the linked 3D scatterplot.
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Figure 11: Relating locations inside the main chamber to their attributes.
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Figure 12: Combining several brushes to extract the eddy: Temperature is brushed using a
histogram (left), the flow direction is defined with
the combined scatterplot (middle) and the result is visualized in the 3D view (right).
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Figure 13: Assigning time to one axis of the 3D scatterplot allows to compare the 2D scatterplots over time.
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This page
is maintained by Harald Piringer.
In case of questions, comments, etc., please
mailto:Piringer@VRVis.at.
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