Streamlining Eye-Tracking and Observational Data for Field Study Visual Analysis
Year: 2025
Type: conference-paper
Abstract: Wearable eye-tracking in field studies presents challenges in synchronising gaze data with dynamic stimuli and integrating observational notes from multiple observers. Existing tools often struggle to visualise eye-tracking patterns in complex, real-world environments with frequently changing areas of interest (AOIs). To address this, we propose a streamlined workflow that simplifies analysis preparation by integrating real-time observer notes with eye-tracking data with enhanced timestamp-based synchronisation, improving data mapping, and automating AOI detection with an energy control room use case. This workflow makes eye-tracking tools like Gazealytics more practical for complex field studies. By streamlining data preparation and automation, our method enhances the scalability and usability of eye-tracking analysis in complex environments, enabling more efficient and accurate visual analysis of real-world decision-making.
Authors: Yidan Zhang, Nethara Athukorala, Ziying Liang, Yidan Qiao, Simran -, Yu Xuan Yio, Lee Lawrence, Benjamin Tag, Mor Vered, Michael Wybrow, Sarah Goodwin
Institutions: Monash University, UNSW Sydney
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4410701932