research-article

Interactions between Inter- and Intra-Individual Effects on Gaze Behavior

Authors:

Christiane B. Wiebel-Herboth,

Martina HasenjägerAuthors Info & Claims

UMAP '20 Adjunct: Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization

Pages 35 - 40

https://doi.org/10.1145/3386392.3397595

Published: 13 July 2020 Publication History

Abstract

Previous work has shown that gaze behavior can vary not only as a function of stimuli and task but also as a function of the observer. Thereby stable inter-individual differences have been shown as well as changes in gaze behavior due to an observer's internal state. How such intra-individual differences interact with inter-individual variations in gaze behavior has not been studied explicitly before. Here, we tackle this question by analyzing fixation statistics and scan path representations in a visual comparison task inducing different observer states. Results show that reliable inter-individual differences exist in fixations statistics and for scan path representations that allow for modeling a longer temporal horizon. Changes in observer state affected the data, but a substantial amount of variance between observers remained stable. We discuss the results in the light of making personalized gaze-based applications more robust against changes in context.

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Cited By

Belardinelli A(2024)Gaze-Based Intention Estimation: Principles, Methodologies, and Applications in HRIACM Transactions on Human-Robot Interaction10.1145/365637613:3(1-30)Online publication date: 26-Sep-2024
https://dl.acm.org/doi/10.1145/3656376
Burlingham CSendhilnathan NWu XMurdison TProulx M(2024)Real-World Scanpaths Exhibit Long-Term Temporal Dependencies: Considerations for Contextual AI for AR ApplicationsProceedings of the 2024 Symposium on Eye Tracking Research and Applications10.1145/3649902.3656352(1-7)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3649902.3656352
Wollstadt PHasenjäger MWiebel-Herboth C(2021)Quantifying the Predictability of Visual Scanpaths Using Active Information StorageEntropy10.3390/e2302016723:2(167)Online publication date: 29-Jan-2021
https://doi.org/10.3390/e23020167
Show More Cited By

Index Terms

Interactions between Inter- and Intra-Individual Effects on Gaze Behavior
1. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

cover image ACM Conferences

UMAP '20 Adjunct: Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization

July 2020

395 pages

ISBN:9781450379502

DOI:10.1145/3386392

Editors:
Tsvi Kuflik
University of Haifa, Israel
,
Ilaria Torre
University of Genoa, Italy
,
Robin Burke
University of Colorado, Boulder, USA
,
Cristina Gena
University of Turin, Italy

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 13 July 2020

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UMAP '20: 28th ACM Conference on User Modeling, Adaptation and Personalization

July 14 - 17, 2020

Genoa, Italy

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Cited By

Belardinelli A(2024)Gaze-Based Intention Estimation: Principles, Methodologies, and Applications in HRIACM Transactions on Human-Robot Interaction10.1145/365637613:3(1-30)Online publication date: 26-Sep-2024
https://dl.acm.org/doi/10.1145/3656376
Burlingham CSendhilnathan NWu XMurdison TProulx M(2024)Real-World Scanpaths Exhibit Long-Term Temporal Dependencies: Considerations for Contextual AI for AR ApplicationsProceedings of the 2024 Symposium on Eye Tracking Research and Applications10.1145/3649902.3656352(1-7)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3649902.3656352
Wollstadt PHasenjäger MWiebel-Herboth C(2021)Quantifying the Predictability of Visual Scanpaths Using Active Information StorageEntropy10.3390/e2302016723:2(167)Online publication date: 29-Jan-2021
https://doi.org/10.3390/e23020167
Wiebel-Herboth CKrüger MWollstadt P(2021)Measuring inter- and intra-individual differences in visual scan patterns in a driving simulator experiment using active information storagePLOS ONE10.1371/journal.pone.024816616:3(e0248166)Online publication date: 18-Mar-2021
https://doi.org/10.1371/journal.pone.0248166

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