TY - GEN
T1 - Visually comparing eye movements over space and time
AU - Kumar, Ayush
AU - Burch, Michael
AU - Mueller, Klaus
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/6/25
Y1 - 2019/6/25
N2 - Analyzing and visualizing eye movement data can provide useful insights into the connectivities and linkings of points and areas of interest (POIs and AOIs). Those typically time-varying relations can give hints about applied visual scanning strategies by either individual or many eye tracked people. However, the challenging issue with this kind of data is its spatio-temporal nature requiring a good visual encoding in order to first, achieve a scalable overview-based diagram, and second, to derive static or dynamic patterns that might correspond to certain comparable visual scanning strategies. To reliably identify the dynamic strategies we describe a visualization technique that generates a more linear representation of the spatio-temporal scan paths. This is achieved by applying different visual encodings of the spatial dimensions that typically build a limitation for an eye movement data visualization causing visual clutter effects, overdraw, and occlusions while the temporal dimension is depicted as a linear time axis. The presented interactive visualization concept is composed of three linked views depicting spatial, metrics-related, as well as distance-based aspects over time.
AB - Analyzing and visualizing eye movement data can provide useful insights into the connectivities and linkings of points and areas of interest (POIs and AOIs). Those typically time-varying relations can give hints about applied visual scanning strategies by either individual or many eye tracked people. However, the challenging issue with this kind of data is its spatio-temporal nature requiring a good visual encoding in order to first, achieve a scalable overview-based diagram, and second, to derive static or dynamic patterns that might correspond to certain comparable visual scanning strategies. To reliably identify the dynamic strategies we describe a visualization technique that generates a more linear representation of the spatio-temporal scan paths. This is achieved by applying different visual encodings of the spatial dimensions that typically build a limitation for an eye movement data visualization causing visual clutter effects, overdraw, and occlusions while the temporal dimension is depicted as a linear time axis. The presented interactive visualization concept is composed of three linked views depicting spatial, metrics-related, as well as distance-based aspects over time.
KW - Eye tracking
KW - Information visualization
KW - Visual analytics
UR - https://www.scopus.com/pages/publications/85069433276
U2 - 10.1145/3317958.3319810
DO - 10.1145/3317958.3319810
M3 - Conference contribution
AN - SCOPUS:85069433276
T3 - Eye Tracking Research and Applications Symposium (ETRA)
BT - Proceedings - ETRA 2019
A2 - Spencer, Stephen N.
PB - Association for Computing Machinery
T2 - 11th ACM Symposium on Eye Tracking Research and Applications, ETRA 2019
Y2 - 25 June 2019 through 28 June 2019
ER -