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16. Dynamic Area of Interest (AOI) Matching in Simulated Environments Via a Direct Coordinate Transform Approach
DescriptionEye tracking is a behavioral sensing modality used widely in human factors research. Area of Interest (AOI) matching is essential for mapping eye-gaze measures to stimuli used in experiments, but dynamic AOI matching--mapping eye-gaze measures to non-stationary stimuli--is particularly challenging to automate. The latter is becoming increasingly important for human factors research in applications such as Level 3 autonomous vehicles. The contribution of this work is a novel method for dynamic AOI matching that is well-suited for environments in which the locations and orientation of objects in the simulated world are known. Importantly, this approach is fully automated and does not rely on machine learning algorithms, thereby improving its speed and robustness to sources of error that may compromise existing methods. We demonstrate the approach by matching gaze data to objects of interest in a driving scenario simulated in Unreal Engine 5 and displayed on multiple screens.
Event Type
Poster
TimeWednesday, September 11th5:30pm - 6:30pm MST
LocationMcArthur Ballroom
Tracks
Aerospace Systems
Cognitive Engineering & Decision Making
Computer Systems
Forensics Professional
Health Care
Human Performance Modeling
Individual Differences in Performance
Perception and Performance
Product Design
Safety
Training
Usability and System Evaluation
Extended Reality