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Demo of the EyeSAC System for Visual Synchronization, Cleaning, and Annotation of Eye Movement Data

  • Ayush Kumar
  • , Debesh Mohanty
  • , Kuno Kurzhals
  • , Fabian Beck
  • , Daniel Weiskopf
  • , Klaus Mueller
  • Stony Brook University
  • Swiss Federal Institute of Technology Zurich
  • University of Duisburg-Essen
  • University of Stuttgart

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

3 Scopus citations

Abstract

Eye movement data analysis plays an important role in examining human cognitive processes and perceptions. Such analysis at times needs data recording from additional sources too during experiments. In this paper, we study a pair programming based collaboration using two eye trackers, stimulus recording, and an external camera recording. To analyze the collected data, we introduce the EyeSAC system that synchronizes the data from different sources and that removes the noisy and missing gazes from eye tracking data with the help of visual feedback from the external recording. The synchronized and cleaned data is further annotated using our system and then exported for further analysis.

Original languageEnglish
Title of host publicationProceedings ETRA 2020 Adjunct - ACM Symposium on Eye Tracking Research and Applications, ETRA 2020
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450371353
DOIs
StatePublished - Jun 2 2020
Event2020 ACM Symposium on Eye Tracking Research and Applications - Adjunct, ETRA 2020 - Virtual, Online, Germany
Duration: Jun 2 2020Jun 5 2020

Publication series

NameEye Tracking Research and Applications Symposium (ETRA)

Conference

Conference2020 ACM Symposium on Eye Tracking Research and Applications - Adjunct, ETRA 2020
Country/TerritoryGermany
CityVirtual, Online
Period06/2/2006/5/20

Keywords

  • Annotation
  • denoising
  • eye tracking
  • filtering
  • synchronization
  • visualization

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