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Journals
Vision
Special Issues
Development of Advanced Eye-tracking Technologies and Applications
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Development of Advanced Eye-tracking Technologies and Applications

A special issue of Vision (ISSN 2411-5150).

Deadline for manuscript submissions: closed (31 August 2018)

Special Issue Editor

Prof. Dr. Moshe Eizenman

E-Mail Website
Guest Editor
Department of Ophthalmology and Vision Sciences, Department of Electrical and Computer Engineering, Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada
Interests: eye tracking; eye movements; visual scanning patterns; detection and estimation

Special Issue Information

Dear Colleagues,

Eye tracking technology is being used in research domains that include neuroscience, psychology, ophthalmology, human factors and marketing. Applications in these domains have been demonstrated largely by experts using specialized and expensive technology. Recent technological advances in computational resources and sensors make it feasible to implement eye-tracking technology on general-purpose low-cost platforms that are widely available. Moreover, advances in machine learning algorithms and visualization techniques improve the capacity to extract information from eye movements and visual scanning patterns. The combined effect of these two technological advances support expanded use of eye tracking technology in vision research, clinical diagnosis and man-machine interfaces.

Prof. Dr. Moshe Eizenman
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Vision is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Remote and head mounted eye tracking technology

  • Mobile eye tracking technology

  • Analysis of visual scanning patterns and eye movements

  • Gaze contingent displays

  • Gaze in augmented and mixed reality systems

  • Novel applications of eye-tracking technology in studies of cognition and attention

  • Novel applications of eye tracking technology in optometry and ophthalmology

  • Novel applications of eye tracking technology in neurology and psychiatry

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

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Research

14 pages, 755 KiB  
Article
Accurate Model-Based Point of Gaze Estimation on Mobile Devices
by Braiden Brousseau, Jonathan Rose and Moshe Eizenman
Vision 2018, 2(3), 35; https://doi.org/10.3390/vision2030035 - 24 Aug 2018
Cited by 15 | Viewed by 5426
Abstract
The most accurate remote Point of Gaze (PoG) estimation methods that allow free head movements use infrared light sources and cameras together with gaze estimation models. Current gaze estimation models were developed for desktop eye-tracking systems and assume that the relative roll between [...] Read more.
The most accurate remote Point of Gaze (PoG) estimation methods that allow free head movements use infrared light sources and cameras together with gaze estimation models. Current gaze estimation models were developed for desktop eye-tracking systems and assume that the relative roll between the system and the subjects’ eyes (the ’R-Roll’) is roughly constant during use. This assumption is not true for hand-held mobile-device-based eye-tracking systems. We present an analysis that shows the accuracy of estimating the PoG on screens of hand-held mobile devices depends on the magnitude of the R-Roll angle and the angular offset between the visual and optical axes of the individual viewer. We also describe a new method to determine the PoG which compensates for the effects of R-Roll on the accuracy of the POG. Experimental results on a prototype infrared smartphone show that for an R-Roll angle of 90 ° , the new method achieves accuracy of approximately 1 ° , while a gaze estimation method that assumes that the R-Roll angle remains constant achieves an accuracy of 3.5 ° . The manner in which the experimental PoG estimation errors increase with the increase in the R-Roll angle was consistent with the analysis. The method presented in this paper can improve significantly the performance of eye-tracking systems on hand-held mobile-devices. Full article
(This article belongs to the Special Issue Development of Advanced Eye-tracking Technologies and Applications)
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