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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.06345 |
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| _version_ | 1866915304393670656 |
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| author | Saxena, Shreshth Visram, Areez Lobo, Neil Mirza, Zahid Khan, Mehak Rafi Pirabaharan, Biranugan Nguyen, Alexander Fink, Lauren K. |
| author_facet | Saxena, Shreshth Visram, Areez Lobo, Neil Mirza, Zahid Khan, Mehak Rafi Pirabaharan, Biranugan Nguyen, Alexander Fink, Lauren K. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_06345 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | SocialEyes: Scaling mobile eye-tracking to multi-person social settings Saxena, Shreshth Visram, Areez Lobo, Neil Mirza, Zahid Khan, Mehak Rafi Pirabaharan, Biranugan Nguyen, Alexander Fink, Lauren K. Human-Computer Interaction Computational Engineering, Finance, and Science Computers and Society Emerging Technologies I.4.8; J.4; J.5; C.4; D.2.10 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. |
| title | SocialEyes: Scaling mobile eye-tracking to multi-person social settings |
| topic | Human-Computer Interaction Computational Engineering, Finance, and Science Computers and Society Emerging Technologies I.4.8; J.4; J.5; C.4; D.2.10 |
| url | https://arxiv.org/abs/2407.06345 |