Computational Measures of Gaze Behavior Using the Concept of Situational Awareness

Yunxiang Jiang, Qing Xu, Aoxing Xu, Simon Parkinson, Klaus Schoeffmann, Chuntie Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Eye gaze is fundamental to common sensorimotor activities. It directly indicates attention and its allocation, making it a critical human factor that reflects cognitive behavior. Data-driven measurements of gaze behavior quantitatively evaluates the allocation of visual attention, indicating the mental and physical activity status of individuals. Situational awareness provides a solid and semantically rich basis for gaze behavior during sensorimotor activities. However, few attempts have been made so far to measure eye gaze data from the perspective of situational awareness. In this paper, we propose four new computational measures of gaze behavior that align with the fundamental concept of situational awareness, effectively measuring the efficiency of visual scanning and sensorimotor activity. Our results have clearly shown that the proposed measures are effective and perform satisfactorily compared to the closely related methods. This work offers a new data-driven approach for biomarker discovery and behavioral biometrics using eye gaze data.
Original languageEnglish
Title of host publicationIEEE International Conference on Multimedia & Expo (ICME) 2025
PublisherIEEE
Publication statusAccepted/In press - 21 Mar 2025
EventIEEE International Conference on Multimedia & Expo - Nantes, France
Duration: 30 Jun 20254 Jul 2025
https://2025.ieeeicme.org/

Conference

ConferenceIEEE International Conference on Multimedia & Expo
Abbreviated titleICME 2025
Country/TerritoryFrance
CityNantes
Period30/06/254/07/25
Internet address

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