Panoptic Visual Analytics of Eye Tracking Data

Valeria Garro, Veronica Sundstedt

2022

Abstract

In eye tracking data visualization, areas of interest (AOIs) are widely adopted to analyze specific regions of the stimulus. We propose a visual analytics tool that leverages panoptic segmentation to automatically divide the whole image or frame video in semantic AOIs. A set of AOI-based visualization techniques are available to analyze the fixation data based on these semantic AOIs. Moreover, we propose a modified version of radial transition graph visualizations adapted to the extracted semantic AOIs and a new visualization technique also based on radial transition graphs. Two application examples illustrate the potential of this approach and are used to discuss its usefulness and limitations.

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Paper Citation


in Harvard Style

Garro V. and Sundstedt V. (2022). Panoptic Visual Analytics of Eye Tracking Data. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, ISBN 978-989-758-555-5, pages 171-178. DOI: 10.5220/0010889500003124


in Bibtex Style

@conference{ivapp22,
author={Valeria Garro and Veronica Sundstedt},
title={Panoptic Visual Analytics of Eye Tracking Data},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,},
year={2022},
pages={171-178},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010889500003124},
isbn={978-989-758-555-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,
TI - Panoptic Visual Analytics of Eye Tracking Data
SN - 978-989-758-555-5
AU - Garro V.
AU - Sundstedt V.
PY - 2022
SP - 171
EP - 178
DO - 10.5220/0010889500003124