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CrowdEyes: Crowdsourcing for robust real-world mobile eye tracking

Lookup NU author(s): Mohammad Othman, Dr Telmo Amaral, Dr Rosin McNaney, Dr Jan Smeddinck, Professor John Vines, Professor Patrick Olivier

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Current eye tracking technologies have a number of drawbacks when it comes to practical use in real-world settings. Common challenges, such as high levels of daylight, eyewear (e.g. spectacles or contact lenses) and eye make-up, give rise to noise that undermines their utility as a standard component for mobile computing, design, and evaluation. To work around these challenges, we introduce CrowdEyes, a mobile eye tracking solution that utilizes crowdsourcing for increased tracking accuracy and robustness. We present a pupil detection task design for crowd workers together with a study that demonstrates the high-level accuracy of crowdsourced pupil detection in comparison to state-of-the-art pupil detection algorithms. We further demonstrate the utility of our crowdsourced analysis pipeline in a fixation tagging task. In this paper, we validate the accuracy and robustness of harnessing the crowd as both an alternative and complement to automated pupil detection algorithms, and explore the associated costs and quality of our crowdsourcing approach.


Publication metadata

Author(s): Othman M, Amaral T, McNaney R, Smeddinck JD, Vines J, Olivier P

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2017

Year of Conference: 2017

Online publication date: 04/09/2017

Acceptance date: 04/09/2017

Publisher: Association for Computing Machinery

URL: https://doi.org/10.1145/3098279.3098559

DOI: 10.1145/3098279.3098559

Data Source Location: http://dx.doi.org/10.17634/122839-1

Library holdings: Search Newcastle University Library for this item

Series Title: Human Computer Interaction with Mobile Devices and Services

Sponsor(s): SIGCHI ACM Special Interest Group on Computer-Human Interaction

ISBN: 9781450350754


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