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SocialEyes: Scaling mobile eye-tracking to multi-person social settings (2407.06345v3)

Published 8 Jul 2024 in cs.HC, cs.CE, cs.CY, and cs.ET

Abstract: Eye movements provide a window into human behaviour, attention, and interaction dynamics. Challenges in real-world, multi-person environments have, however, restrained eye-tracking research predominantly to single-person, in-lab settings. We developed a system to stream, record, and analyse synchronised data from multiple mobile eye-tracking devices during collective viewing experiences (e.g., concerts, films, lectures). We implemented lightweight operator interfaces for real-time-monitoring, remote-troubleshooting, and gaze-projection from individual egocentric perspectives to a common coordinate space for shared gaze analysis. We tested the system in a live concert and a film screening with 30 simultaneous viewers during each of two public events (N=60). We observe precise time-synchronisation between devices measured through recorded clock-offsets, and accurate gaze-projection in challenging dynamic scenes. Our novel analysis metrics and visualizations illustrate the potential of collective eye-tracking data for understanding collaborative behaviour and social interaction. This advancement promotes ecological validity in eye-tracking research and paves the way for innovative interactive tools.

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Authors (8)
  1. Shreshth Saxena (1 paper)
  2. Areez Visram (1 paper)
  3. Neil Lobo (1 paper)
  4. Zahid Mirza (1 paper)
  5. Mehak Rafi Khan (1 paper)
  6. Biranugan Pirabaharan (1 paper)
  7. Alexander Nguyen (1 paper)
  8. Lauren K. Fink (1 paper)

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