A Four-level Focus+Context Approach to Interactive Visual
Analysis of Temporal Features in Large Scientific Data
Philipp Muigg, Johannes Kehrer, Steffen Oeltze,
Harald Piringer, Helmut Doleisch, Bernhard Preim, Helwig Hauser
ARTICLE,
Computer Graphics Forum,
may, 2008
AbstractIn this paper we present a new approach to the interactive visual
analysis of time-dependent scientific data – both from measurements as well
as from computational simulation – by visualizing a scalar function over time
for each of tenthousands or even millions of sample points. In order to cope
with overdrawing and cluttering, we introduce a new four-level method of
focus+context visualization. Based on a setting of coordinated, multiple views
(with linking and brushing), we integrate three different kinds of focus and
also the context in every single view. Per data item we use three values (from
the unit interval each) to represent to which degree the data item is part of
the respective focus level. We present a color compositing scheme which is
capable of expressing all three values in a meaningful way, taking semantics
and their relations amongst each other (in the context of our multiple linked
view setup) into account. Furthermore, we present additional image-based
postprocessing methods to enhance the visualization of large sets of function
graphs, including a texture-based technique based on line integral convolution
(LIC). We also propose advanced brushing techniques which are specific to the
timedependent nature of the data (in order to brush patterns over time more
efficiently). We demonstrate the usefulness of the new approach in the context
of medical perfusion data.
Published
Computer Graphics Forum
Media
BibTeX
@article{Muigg08four,
author = {Philipp Muigg and Johannes Kehrer and Steffen Oeltze and
Harald Piringer and Helmut Doleisch and Bernhard Preim and Helwig Hauser},
title = {A Four-level Focus+Context Approach to Interactive Visual
Analysis of Temporal Features in Large Scientific Data},
year = {2008},
month = {may},
abstract = {In this paper we present a new approach to the interactive visual
analysis of time-dependent scientific data – both from measurements as well
as from computational simulation – by visualizing a scalar function over time
for each of tenthousands or even millions of sample points. In order to cope
with overdrawing and cluttering, we introduce a new four-level method of
focus+context visualization. Based on a setting of coordinated, multiple views
(with linking and brushing), we integrate three different kinds of focus and
also the context in every single view. Per data item we use three values (from
the unit interval each) to represent to which degree the data item is part of
the respective focus level. We present a color compositing scheme which is
capable of expressing all three values in a meaningful way, taking semantics
and their relations amongst each other (in the context of our multiple linked
view setup) into account. Furthermore, we present additional image-based
postprocessing methods to enhance the visualization of large sets of function
graphs, including a texture-based technique based on line integral convolution
(LIC). We also propose advanced brushing techniques which are specific to the
timedependent nature of the data (in order to brush patterns over time more
efficiently). We demonstrate the usefulness of the new approach in the context
of medical perfusion data.},
journal = {Computer Graphics Forum},
event = "EuroVis 2008",
volume = {27},
number = {3},
pages = {775--782},
location = "Eindhooven, Netherlands",
URL = {http://dx.doi.org/10.1111/j.1467-8659.2008.01207.x},
}
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