@phdthesis{Viola:2005:IDE,
month = may,
optwww = {},
author = {Ivan Viola},
optkey = {},
optannote = {},
opttype = {},
url = {http://www.cg.tuwien.ac.at/research/publications/2005/phd-viola/},
title = {{I}mportance-{D}riven {E}xpressive {V}isualization},
abstract = {In this thesis several expressive visualization techniques for
volumetric data are presented. The key idea is to classify the
underlying data according to its prominence on the resulting
visualization by importance value. The importance property drives
the visualization pipeline to emphasize the most prominent
features and to suppress the less relevant ones. The suppression
can be realized globally, so the whole object is suppressed, or
locally. A local modulation generates cut-away and ghosted views
because the suppression of less relevant features occurs only on
the part where the occlusion of more important features appears.
Features within the volumetric data are classified according to a
new dimension denoted as object importance. This property
determines which structures should be readily discernible and
which structures are less important. Next, for each feature
various representations (levels of sparseness) from a dense to a
sparse depiction are defined. Levels of sparseness define a
spectrum of optical properties or rendering styles. The resulting
image is generated by ray-casting and combining the intersected
features proportional to their importance. An additional step to
traditional volume rendering evaluates the areas of occlusion and
assigns a particular level of sparseness. This step is denoted as
importance compositing. Advanced schemes for importance
compositing determine the resulting visibility of features and if
the resulting visibility distribution does not correspond to the
importance distribution different levels of sparseness are
selected. The applicability of importance-driven visualization is
demonstrated on several examples from medical diagnostics
scenarios, flow visualization, and interactive illustrative
visualization.},
school = {Technische Universit{\"a}t Wien},
address = {Austria},
localfile = {papers/Viola.2005.IDE.pdf},
year = {2005},
}
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