Information
- Publication Type: Invited Talk
- Workgroup(s)/Project(s):
- Date: 31. August 2017
- Date (from): 31. August 2017
- Date (to): 31. August 2017
- Event: Visit of University of Konstanz
- Location: University of Konstanz
Abstract
Visual computing uses computer-supported, interactive, visual representations of (abstract) data to amplify cognition. In recent years data complexity concerning volume, veracity, velocity, and variety has increased considerably. Several adaptive visual computing approaches are discussed in detail. Data-sensitive navigation for user-interface elements is presented. The approach normalizes user input according to visual change, and also visually communicates this normalization. In this way, output-sensitive interactions can be realized. Quantitative and reproducible linking & brushing as integral part of visual analytics is approached through structured brushing, percentile brushes, linked statistics, and change visualization. Multiscale models, e.g., from structural biology, require multiscale dynamic color mapping with sometimes overlapping or contradicting colors. We present a technique, which adaptively, based on the current scale level, nonlinearly and seamlessly adjusts the color scheme to depict or distinguish the currently best visible structural information. Adaptive visual computing is addressing the amplified data complexity through increased scalability. Research challenges and directions are sketched at the end of the talk.
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BibTeX
@talk{Groeller-2017-AVC,
title = "Adaptive Visual Computing",
author = "Meister Eduard Gr\"{o}ller",
year = "2017",
abstract = "Visual computing uses computer-supported, interactive,
visual representations of (abstract) data to amplify
cognition. In recent years data complexity concerning
volume, veracity, velocity, and variety has increased
considerably. Several adaptive visual computing approaches
are discussed in detail. Data-sensitive navigation for
user-interface elements is presented. The approach
normalizes user input according to visual change, and also
visually communicates this normalization. In this way,
output-sensitive interactions can be realized. Quantitative
and reproducible linking & brushing as integral part of
visual analytics is approached through structured brushing,
percentile brushes, linked statistics, and change
visualization. Multiscale models, e.g., from structural
biology, require multiscale dynamic color mapping with
sometimes overlapping or contradicting colors. We present a
technique, which adaptively, based on the current scale
level, nonlinearly and seamlessly adjusts the color scheme
to depict or distinguish the currently best visible
structural information. Adaptive visual computing is
addressing the amplified data complexity through increased
scalability. Research challenges and directions are sketched
at the end of the talk. ",
month = aug,
event = "Visit of University of Konstanz",
location = "University of Konstanz",
URL = "https://www.cg.tuwien.ac.at/research/publications/2017/Groeller-2017-AVC/",
}