Doctor's Theses (authored and supervised):
"Using and Adapting to Limits of Human Perception in Visualization";
Supervisor, Reviewer: I. Viola, P. Isenberg, K. Myszkowski;
Institut für Computergraphik und Algorithmen,
oral examination: 2017-11-06.
When analyzing a visualization, the user must often find or compare important objects.
This analysis suffers from a fundamental problem: data sets are becoming larger and
larger, leading to more visual clutter. This makes it very hard to find the objects the
user is interested in. Part of this problem originates in the human visual system, which
is limited through the bandwith of visual light, visual resolution, and the processing
capabilities of the human mind.
In this thesis, three methods are shown that adapt to these limitations,and use them
to the advantage. The first method targets people with color vision deficiency (CVD),
such as red-green blindness. People with CVD have difficulty discerning colors. The aim
of this method is to adapt a color map to the individual and maximize the use of their
personal color space. The second method offers a dynamic use of the color space for large
hierarchical data. During interactive exploration of the data, the color mapping adapts
on-the-fly to the current view position. We make use of "inattentional blindness"-i.e.,
not noticing changes that are not focused on-in order to make the change in color very
subtle. The third method uses flicker in order to subtly draw attention to parts of a scene.
We use the fact that the "critical fusion frequency"-the frequency at which flickering
becomes a stable signal-varies across the retina. Using a high frequency monitor and
empirical measurements, we created a method that can draw attention to objects and
can only be seen in the peripheral vision, but not in the foveal vision.
Electronic version of the publication:
Created from the Publication Database of the Vienna University of Technology.