May 2003
Volume 44, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2003
Wide Field 3D Gaze Tracking System
Author Affiliations & Notes
  • J. Barabas
    Schepens Eye Research Institute, Harvard Medical School, Boston, MA, United States
  • R. Giorgi
    Schepens Eye Research Institute, Harvard Medical School, Boston, MA, United States
  • R.B. Goldstein
    Schepens Eye Research Institute, Harvard Medical School, Boston, MA, United States
  • H. Apfelbaum
    Schepens Eye Research Institute, Harvard Medical School, Boston, MA, United States
  • R.L. Woods
    Schepens Eye Research Institute, Harvard Medical School, Boston, MA, United States
  • E. Peli
    Schepens Eye Research Institute, Harvard Medical School, Boston, MA, United States
  • Footnotes
    Commercial Relationships  J. Barabas, None; R. Giorgi, None; R.B. Goldstein, None; H. Apfelbaum, None; R.L. Woods, None; E. Peli, None.
  • Footnotes
    Support  NIH Grant EY12890
Investigative Ophthalmology & Visual Science May 2003, Vol.44, 1965. doi:
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    • Get Citation

      J. Barabas, R. Giorgi, R.B. Goldstein, H. Apfelbaum, R.L. Woods, E. Peli; Wide Field 3D Gaze Tracking System . Invest. Ophthalmol. Vis. Sci. 2003;44(13):1965.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Abstract: : Purpose: Current gaze-tracking systems can monitor point of gaze allowing for free head movement, but do not perform well when used with the large display surfaces and wide range of head positions needed for presentation of wide-field experimental stimuli. We developed a novel system for monitoring a subject's gaze, providing accurate eye location and orientation recordings over the large spaces needed for action and motion experiments. This system allows for complete calibration from only a short series of directed gazes and requires almost no physical measurement. Methods: The gaze tracking system consisted of an ISCAN head mounted pupil tracker and an Ascension Flock of Birds position sensor with Extended Range Transmitter. Data from the position sensor were compensated for magnetic distortion using a polynomial correction function. Gaze was computed based on measurements from the two sensors using a geometric model. The thirteen parameters of the gaze computation model were found using a nonlinear regression technique. The calibration technique was verified using human subjects, and using a laser mounted in a foam mannequin head. Results: Our implementation of the system allowed for tracking of gaze of subjects walking on a treadmill. Subject head positions covered a volume of 2 cubic meters. Mean gaze error within this volume was less than 2 degrees. Eye movements were recorded at a rate of 60Hz, limited only by the speed of the ISCAN pupil tracker. Recordings of head position, vector of gaze and exact eye location were made simultaneously. Conclusion: A flexible, accurate system for recording head and eye movements in response to large stimuli has been developed using standard hardware systems.

Keywords: eye movements: recording techniques • computational modeling • vision and action 
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