Bridging the gap between eye tracking and crowdsourcing

Pierre Lebreton, Toni Mäki, Evangelos Skodras, Isabelle Hupont, Matthias Hirth

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

12 Citations (Scopus)

Abstract

Visual attention constitutes a very important feature of the human visual system (HVS). Every day when watching videos, images or browsing the Internet, people are confronted with more information than they are able to process, and analyze only part of the information in front of them. In parallel, crowdsourcing has become a particularly hot topic, enabling to scale subjective experiments to a large crowd with diversity in terms of nationalities, social background, age, etc. This paper describes a novel framework with the aim to bridge these two fields, by providing a new way of measurements of user's experience in a subjective crowdsourcing experiment. This study goes beyond self-reported methods, and provide a new kind of information for the context of crowdsourcing: visual attention. The results show that it is possible to estimate visual attention, in a non-intrusive manner and without using self-reported methods or specialized equipment, with a precision as high as 14.1% in the horizontal axis and 17.9% in the vertical axis. This accuracy is sufficient for many kinds of measurements that can be efficiently executed only in non-controlled environments.
Original languageEnglish
Title of host publicationHuman Vision and Electronic Imaging XX
PublisherInternational Society for Optics and Photonics SPIE
DOIs
Publication statusPublished - 2015
MoE publication typeA4 Article in a conference publication
EventHuman Vision and Electronic Imaging XX - San Francisco, United States
Duration: 9 Feb 201512 Feb 2015

Publication series

SeriesProceedings of SPIE
Volume9394
ISSN0277-786X

Conference

ConferenceHuman Vision and Electronic Imaging XX
Country/TerritoryUnited States
CitySan Francisco
Period9/02/1512/02/15

Keywords

  • crowdsourcing
  • extend measurements
  • eye tracking
  • human computer interaction
  • visual attention
  • webRTC

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