%0 Conference Paper %1 8f1c1c0fd2ca4873996297fec4e45553 %A Netzel, Rudolf %A Weiskopf, Daniel %B Proceedings of the Symposium on Eye Tracking and Visualization (ETVIS) %D 2016 %E 2016, ETVIS %K 2016 B01 from:mueller sfbtrr161 vis(us) visus visus:netzelrf visus:weiskopf %P 21-25 %R 10.1109/ETVIS.2016.7851160 %T Hilbert Attention Maps for Visualizing Spatiotemporal Gaze Data %U https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7851160 %X Attention maps-often in the form of heatmaps-are a common visualization approach to obtaining an overview of the spatial distribution of gaze data from eye tracking experiments. However, attention maps are not designed to let us easily analyze the temporal information of gaze data: they completely ignore temporal information by aggregating over time, or they use animation to build a sequence of attention maps. To overcome this issue, we introduce Hilbert attention maps: a 2D static visualization of the spatiotemporal distribution of gaze points. The visualization is based on the projection of the 2D spatial domain onto a space-filling Hilbert curve that is used as one axis of our new attention map; the other axis represents time. We visualize Hilbert attention maps either as dot displays or heatmaps. This 2D visualization works for data from individual participants or large groups of participants, it supports static and dynamic stimuli alike, and it does not require any preprocessing or definition of areas of interest. We demonstrate how our visualization allows analysts to identify spatiotemporal patterns of visual reading behavior, including attentional synchrony and smooth pursuit.

@inproceedings{8f1c1c0fd2ca4873996297fec4e45553, abstract = {Attention maps-often in the form of heatmaps-are a common visualization approach to obtaining an overview of the spatial distribution of gaze data from eye tracking experiments. However, attention maps are not designed to let us easily analyze the temporal information of gaze data: they completely ignore temporal information by aggregating over time, or they use animation to build a sequence of attention maps. To overcome this issue, we introduce Hilbert attention maps: a 2D static visualization of the spatiotemporal distribution of gaze points. The visualization is based on the projection of the 2D spatial domain onto a space-filling Hilbert curve that is used as one axis of our new attention map; the other axis represents time. We visualize Hilbert attention maps either as dot displays or heatmaps. This 2D visualization works for data from individual participants or large groups of participants, it supports static and dynamic stimuli alike, and it does not require any preprocessing or definition of areas of interest. We demonstrate how our visualization allows analysts to identify spatiotemporal patterns of visual reading behavior, including attentional synchrony and smooth pursuit.}, added-at = {2020-10-09T12:34:23.000+0200}, author = {Netzel, Rudolf and Weiskopf, Daniel}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2b081a6756fadaf1bfe7beedc7b004add/mueller}, booktitle = {Proceedings of the Symposium on Eye Tracking and Visualization (ETVIS)}, description = {Hilbert Attention Maps for Visualizing Spatiotemporal Gaze Data}, doi = {10.1109/ETVIS.2016.7851160}, editor = {2016, ETVIS}, interhash = {0e03ce36db7577bee2399c65e7595b50}, intrahash = {b081a6756fadaf1bfe7beedc7b004add}, keywords = {2016 B01 from:mueller sfbtrr161 vis(us) visus visus:netzelrf visus:weiskopf}, pages = {21-25}, timestamp = {2020-10-09T10:34:23.000+0200}, title = {Hilbert Attention Maps for Visualizing Spatiotemporal Gaze Data}, url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7851160}, year = 2016 }