Motion tracking of iris features to detect small eye movements

The inability of current video-based eye trackers to reliably detect very small eye movements has led to confusion about the prevalence or even the existence of monocular microsaccades (small, rapid eye movements that occur in only one eye at a time). As current methods often rely on precisely local...

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Autores principales: Chaudhary, Aayush K., Pelz, Jeff B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bern Open Publishing 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7962675/
https://www.ncbi.nlm.nih.gov/pubmed/33828748
http://dx.doi.org/10.16910/jemr.12.6.4
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author Chaudhary, Aayush K.
Pelz, Jeff B.
author_facet Chaudhary, Aayush K.
Pelz, Jeff B.
author_sort Chaudhary, Aayush K.
collection PubMed
description The inability of current video-based eye trackers to reliably detect very small eye movements has led to confusion about the prevalence or even the existence of monocular microsaccades (small, rapid eye movements that occur in only one eye at a time). As current methods often rely on precisely localizing the pupil and/or corneal reflection on successive frames, current microsaccade-detection algorithms often suffer from signal artifacts and a low signal-to-noise ratio. We describe a new video-based eye tracking methodology which can reliably detect small eye movements over 0.2 degrees (12 arcmins) with very high confidence. Our method tracks the motion of iris features to estimate velocity rather than position, yielding a better record of microsaccades. We provide a more robust, detailed record of miniature eye movements by relying on more stable, higher-order features (such as local features of iris texture) instead of lower-order features (such as pupil center and corneal reflection), which are sensitive to noise and drift.
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spelling pubmed-79626752021-04-06 Motion tracking of iris features to detect small eye movements Chaudhary, Aayush K. Pelz, Jeff B. J Eye Mov Res Research Article The inability of current video-based eye trackers to reliably detect very small eye movements has led to confusion about the prevalence or even the existence of monocular microsaccades (small, rapid eye movements that occur in only one eye at a time). As current methods often rely on precisely localizing the pupil and/or corneal reflection on successive frames, current microsaccade-detection algorithms often suffer from signal artifacts and a low signal-to-noise ratio. We describe a new video-based eye tracking methodology which can reliably detect small eye movements over 0.2 degrees (12 arcmins) with very high confidence. Our method tracks the motion of iris features to estimate velocity rather than position, yielding a better record of microsaccades. We provide a more robust, detailed record of miniature eye movements by relying on more stable, higher-order features (such as local features of iris texture) instead of lower-order features (such as pupil center and corneal reflection), which are sensitive to noise and drift. Bern Open Publishing 2019-04-05 /pmc/articles/PMC7962675/ /pubmed/33828748 http://dx.doi.org/10.16910/jemr.12.6.4 Text en This work is licensed under a Creative Commons Attribution 4.0 International License, ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Research Article
Chaudhary, Aayush K.
Pelz, Jeff B.
Motion tracking of iris features to detect small eye movements
title Motion tracking of iris features to detect small eye movements
title_full Motion tracking of iris features to detect small eye movements
title_fullStr Motion tracking of iris features to detect small eye movements
title_full_unstemmed Motion tracking of iris features to detect small eye movements
title_short Motion tracking of iris features to detect small eye movements
title_sort motion tracking of iris features to detect small eye movements
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7962675/
https://www.ncbi.nlm.nih.gov/pubmed/33828748
http://dx.doi.org/10.16910/jemr.12.6.4
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