1999
DOI: 10.1016/s0169-2607(98)00105-9
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Robust pupil center detection using a curvature algorithm

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Cited by 101 publications
(44 citation statements)
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“…Pupil size was determined by both center-of-mass and ellipse-fit methods at a rate of 200 Hz. [20][21][22] Both measures yield identical results, so center-of-mass calculations were used when pupil images were not obstructed by eyelids or lashes, and ellipse-fit calculations were used for obstructed images.…”
Section: Methodsmentioning
confidence: 99%
“…Pupil size was determined by both center-of-mass and ellipse-fit methods at a rate of 200 Hz. [20][21][22] Both measures yield identical results, so center-of-mass calculations were used when pupil images were not obstructed by eyelids or lashes, and ellipse-fit calculations were used for obstructed images.…”
Section: Methodsmentioning
confidence: 99%
“…Measurements of the pupil diameter have been performed by a two steps procedure: first, the points laying on the pupil boundary have been detected by using a curvature algorithm [10]; these points have been then interpolated according to the method of Chauduri and Kundu [11], based on an optimum weighted least square circular fitting.…”
Section: B Estimation Of Pupil Diametermentioning
confidence: 99%
“…The curvature algorithm [10] detect pupil center. The accuracy rate is 40% which is detected pupil boundary in an error of less 0.1 degrees.…”
Section: Literature Reviewmentioning
confidence: 99%