Fraunhofer-Gesellschaft

Publica

Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten.

A task-based view on the visual analysis of eye-tracking data

 
: Kurzhals, K.; Burch, M.; Blascheck, T.; Andrienko, G.; Andrienko, N.; Weiskopf, D.

:

Burch, M.:
Eye tracking and visualization. Foundations, techniques, and applications : ETVIS 2015, The First Workshop on Eye Tracking and Visualization (ETVIS); The workshop took place in Chicago, Illinois, USA, on October 25, 2015
Cham: Springer International Publishing, 2017 (Mathematics and visualization)
ISBN: 978-3-319-47023-8 (Print)
ISBN: 978-3-319-47024-5 (Online)
S.3-22
Workshop on Eye Tracking and Visualization (ETVIS) <1, 2015, Chicago/Ill.>
Deutsche Forschungsgemeinschaft DFG
EXC 310
European Commission EC
H2020; 687591; datAcron
Big Data Analytics for Time Critical Mobility Forecasting
European Commission EC
H2020; 688380; VaVeL
Variety, Veracity, VaLue: Handling the Multiplicity of Urban Sensors
Englisch
Konferenzbeitrag
Fraunhofer IAIS ()

Abstract
The visual analysis of eye movement data has become an emerging field of research leading to many new visualization techniques in recent years. These techniques provide insight beyond what is facilitated by traditional attention maps and gaze plots, providing important means to support statistical analysis and hypothesis building. There is no single "all-in-one" visualization to solve all possible analysis tasks. In fact, the appropriate choice of a visualization technique depends on the type of data and analysis task. We provide a taxonomy of analysis tasks that is derived from literature research of visualization techniques and embedded in our pipeline model of eye-tracking visualization. Our task taxonomy is linked to references to representative visualization techniques and, therefore, it is a basis for choosing appropriate methods of visual analysis. We also elaborate on how far statistical analysis with eye-tracking metrics can be enriched by suitable visualization and visual analytics techniques to improve the extraction of knowledge during the analysis process.

: http://publica.fraunhofer.de/dokumente/N-480941.html