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Measuring torsional eye movements by tracking stable iris features.

Ong JK, Haslwanter T - J. Neurosci. Methods (2010)

Bottom Line: We propose a new method to measure torsional eye movements from videos taken of the eye.In this method, we track iris features that have been identified as Maximally Stable Volumes.These features, which are stable over time, are dark regions with bright borders that are steep in intensity.

View Article: PubMed Central - PubMed

Affiliation: Institute of Medical Device Engineering, FH OO Forschungs & Entwicklungs GmbH, Upper Austria University of Applied Sciences, Garnisonstr 21, 4020 Linz, Austria. james.ong@fh-linz.at

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Effect of error in the pupil position on torsion estimates. Here, we added an error of 3 or 6 raw pixels to the pupil centre estimates, which correspond to an error of 1° and 2° of gaze angle, respectively. The resulting torsion estimates remain very close to the original torsion estimate.
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fig0020: Effect of error in the pupil position on torsion estimates. Here, we added an error of 3 or 6 raw pixels to the pupil centre estimates, which correspond to an error of 1° and 2° of gaze angle, respectively. The resulting torsion estimates remain very close to the original torsion estimate.

Mentions: We used the same head-rolling video to check the sensitivity of our method to errors in the estimated pupil centre position. Here, we simply added artificial shifts (1° and 2° of gaze angle) to the pupil centre estimates before performing the polar transform on the images. In Fig. 4, the resulting torsion estimates are shown. The curves all show the same qualitative behaviour and the maximum torsional error is only 0.5°, even with 2° error in gaze direction. This shows that our method is robust to small errors in the pupil fits.


Measuring torsional eye movements by tracking stable iris features.

Ong JK, Haslwanter T - J. Neurosci. Methods (2010)

Effect of error in the pupil position on torsion estimates. Here, we added an error of 3 or 6 raw pixels to the pupil centre estimates, which correspond to an error of 1° and 2° of gaze angle, respectively. The resulting torsion estimates remain very close to the original torsion estimate.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2958308&req=5

fig0020: Effect of error in the pupil position on torsion estimates. Here, we added an error of 3 or 6 raw pixels to the pupil centre estimates, which correspond to an error of 1° and 2° of gaze angle, respectively. The resulting torsion estimates remain very close to the original torsion estimate.
Mentions: We used the same head-rolling video to check the sensitivity of our method to errors in the estimated pupil centre position. Here, we simply added artificial shifts (1° and 2° of gaze angle) to the pupil centre estimates before performing the polar transform on the images. In Fig. 4, the resulting torsion estimates are shown. The curves all show the same qualitative behaviour and the maximum torsional error is only 0.5°, even with 2° error in gaze direction. This shows that our method is robust to small errors in the pupil fits.

Bottom Line: We propose a new method to measure torsional eye movements from videos taken of the eye.In this method, we track iris features that have been identified as Maximally Stable Volumes.These features, which are stable over time, are dark regions with bright borders that are steep in intensity.

View Article: PubMed Central - PubMed

Affiliation: Institute of Medical Device Engineering, FH OO Forschungs & Entwicklungs GmbH, Upper Austria University of Applied Sciences, Garnisonstr 21, 4020 Linz, Austria. james.ong@fh-linz.at

Show MeSH
Related in: MedlinePlus