Open Access
2 March 2018 Robust eye tracking based on multiple corneal reflections for clinical applications
Clara Mestre, Josselin Gautier, Jaume Pujol
Author Affiliations +
Funded by: Spanish Ministry of Economy and Competitiveness, European Union, Davalor Salud, Generalitat de Catalunya
Abstract
A set of methods in terms of both image processing and gaze estimation for accurate eye tracking is proposed. The eye-tracker used in this study relies on the dark-pupil method with up to 12 corneal reflections and offers an unprecedented high resolution imaging of the pupil and the cornea. The potential benefits of a higher number of glints and their optimum arrangement are analyzed considering distinct light sources configurations with 12, 8, 6, 4, and 2 corneal reflections. Moreover, a normalization factor of the pupil-glint vector is proposed for each configuration. There is a tendency for increasing accuracy with the number of glints, especially vertically (0.47 deg for 12 glints configuration versus 0.65 deg for 2 glints configuration). Besides the number of corneal reflections, their arrangement seems to have a stronger effect. A configuration that minimizes the interference of the eyelids with the corneal reflections is desired. Finally, the normalization of the pupil-glint vectors improves the vertical eye tracking accuracy up to 43.2%. In addition, the normalization also limits the need for a higher number of light sources to achieve better spatial accuracy.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE) 1083-3668/2018/$25.00 © 2018 SPIE
Clara Mestre, Josselin Gautier, and Jaume Pujol "Robust eye tracking based on multiple corneal reflections for clinical applications," Journal of Biomedical Optics 23(3), 035001 (2 March 2018). https://doi.org/10.1117/1.JBO.23.3.035001
Received: 10 October 2017; Accepted: 1 February 2018; Published: 2 March 2018
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CITATIONS
Cited by 12 scholarly publications and 2 patents.
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KEYWORDS
Eye

Head

Light sources

Calibration

Image processing

Light emitting diodes

Cameras

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