CrowdEyes: crowdsourcing for robust real-world mobile eye tracking

Roisin McNaney, Mohammad Othman, Telmo Amaral, Jan Smeddinck, John Vines, Patrick Olivier

Research output: Contribution to conferenceConference Paperpeer-review

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 (eg 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 …
Original languageEnglish
Pages18
Number of pages10
Publication statusPublished - 2017
EventProceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services: MobileHCI -
Duration: 4 Sep 2017 → …

Conference

ConferenceProceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services
Period4/09/17 → …

Structured keywords

  • Digital Health

Keywords

  • crowdsourcing
  • Eye-tracking
  • HCI

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