Uncertainty-Aware Scarf Plots

Fuente: arXiv
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Bibliographic Details
Main Authors: Pathmanathan, Nelusa, Öney, Seyda, Koch, Maurice, Weiskopf, Daniel, Kurzhals, Kuno
Format: Preprint
Published: 2025
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author Pathmanathan, Nelusa
Öney, Seyda
Koch, Maurice
Weiskopf, Daniel
Kurzhals, Kuno
author_facet Pathmanathan, Nelusa
Öney, Seyda
Koch, Maurice
Weiskopf, Daniel
Kurzhals, Kuno
contents Multiple challenges emerge when analyzing eye-tracking data with areas of interest (AOIs) because recordings are subject to different sources of uncertainties. Previous work often presents gaze data without considering those inaccuracies in the data. To address this issue, we developed uncertainty-aware scarf plot visualizations that aim to make analysts aware of uncertainties with respect to the position-based mapping of gaze to AOIs and depth dependency in 3D scenes. Additionally, we also consider uncertainties in automatic AOI annotation. We showcase our approach in comparison to standard scarf plots in an augmented reality scenario.
format Preprint
id arxiv_https___arxiv_org_abs_2505_05038
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Uncertainty-Aware Scarf Plots
Pathmanathan, Nelusa
Öney, Seyda
Koch, Maurice
Weiskopf, Daniel
Kurzhals, Kuno
Human-Computer Interaction
Multiple challenges emerge when analyzing eye-tracking data with areas of interest (AOIs) because recordings are subject to different sources of uncertainties. Previous work often presents gaze data without considering those inaccuracies in the data. To address this issue, we developed uncertainty-aware scarf plot visualizations that aim to make analysts aware of uncertainties with respect to the position-based mapping of gaze to AOIs and depth dependency in 3D scenes. Additionally, we also consider uncertainties in automatic AOI annotation. We showcase our approach in comparison to standard scarf plots in an augmented reality scenario.
title Uncertainty-Aware Scarf Plots
topic Human-Computer Interaction
url https://arxiv.org/abs/2505.05038