A Multimodal Eye Movement Dataset and a Multimodal Eye Movement Segmentation Analysis

Wolfgang Fuhl, Enkelejda Kasneci

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

4 Scopus citations

Abstract

We present a new dataset with annotated eye movements. The dataset consists of over 800,000 gaze points recorded during a car ride in the real world and in the simulator. In total, the eye movements of 19 subjects were annotated. In this dataset, there are several data sources including the eyelid closure, the pupil center, the optical vector, and a vector into the pupil center starting from the center of the eye corners. These different data sources are analyzed and evaluated individually as well as in combination with respect to their suitability for eye movement classification. These results will help developers of real-time systems and algorithms to find the best data sources for their application. Also, new algorithms can be trained and evaluated on this data set. Link to code and dataset https://atreus.informatik.uni-tuebingen.de/seafile/d/8e2ab8c3fdd444e1a135/?p=%2FA%20Multimodal%20Eye%20Movement%20Dataset%20and%20...mode=list

Original languageEnglish
Title of host publicationProceedings - ETRA 2021
Subtitle of host publicationACM Symposium on Eye Tracking Research and Applications, Short Papers Proceedings
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450383455
DOIs
StatePublished - 25 May 2021
Externally publishedYes
Event2021 ACM Symposium on Eye Tracking Research and Applications, ETRA 2021 - Virtual, Online, United Kingdom
Duration: 24 May 202127 May 2021

Publication series

NameEye Tracking Research and Applications Symposium (ETRA)
VolumePartF169257

Conference

Conference2021 ACM Symposium on Eye Tracking Research and Applications, ETRA 2021
Country/TerritoryUnited Kingdom
CityVirtual, Online
Period24/05/2127/05/21

Keywords

  • Classification
  • Data set
  • Driving
  • Eye Movements
  • Machine Learning
  • Real World
  • Segmentation

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