Webcam eye tracking close to laboratory standards: Comparing a new webcam-based system and the EyeLink 1000

• Published in: Behavior research methods Vol. 56; no. 5; pp. 5002 - 5022
• Main Authors: Kaduk, Tobiasz, Goeke, Caspar, Finger, Holger, König, Peter
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.08.2024
• Subjects: Adult; Behavioral Science and Psychology; Cognitive Psychology; Eye Movements - physiology; Eye-Tracking Technology; Female; Head Movements - physiology; Humans; Male; Original Manuscript; Psychology; Pursuit, Smooth - physiology; Young Adult; Webcam based eyetracker; Online testing; Labvanced; Eyetracking comparison
• ISSN: 1554-3528; 1554-351X; 1554-3528
• DOI: 10.3758/s13428-023-02237-8

This paper aims to compare a new webcam-based eye-tracking system, integrated into the Labvanced platform for online experiments, to a “gold standard” lab-based eye tracker (EyeLink 1000 - SR Research). Specifically, we simultaneously recorded data with both eye trackers in five different tasks, analyzing their real-time performance. These tasks were a subset of a standardized test battery for eye trackers, including a Large Grid task, Smooth Pursuit eye movements, viewing natural images, and two Head Movements tasks (roll, yaw). The results show that the webcam-based system achieved an overall accuracy of 1.4°, and a precision of 1.1° (standard deviation (SD) across subjects), an error of about 0.5° larger than the EyeLink system. Interestingly, both accuracy (1.3°) and precision (0.9°) were slightly better for centrally presented targets, the region of interest in many psychophysical experiments. Remarkably, the correlation of raw gaze samples between the EyeLink and webcam-based was at about 90% for the Large Grid task and about 80% for Free View and Smooth Pursuit. Overall, these results put the performance of the webcam-based system roughly on par with mobile eye-tracking devices (Ehinger et al. PeerJ , 7 , e7086, 2019 ; Tonsen et al., 2020 ) and demonstrate substantial improvement compared to existing webcam eye-tracking solutions (Papoutsaki et al., 2017 ).