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Algorithmic gaze classification for mobile eye-tracking

Published: 25 May 2021 Publication History

Abstract

Mobile eye tracking traditionally requires gaze to be coded manually. We introduce an open-source Python package (GazeClassify) that algorithmically annotates mobile eye tracking data for the study of human interactions. Instead of manually identifying objects and identifying if gaze is directed towards an area of interest, computer vision algorithms are used for the identification and segmentation of human bodies. To validate the algorithm, mobile eye tracking data from short combat sport sequences were analyzed. The performance of the algorithm was compared against three manual raters. The algorithm performed with substantial reliability in comparison to the manual raters when it came to annotating which area of interest gaze was closest to. However, the algorithm was more conservative than the manual raters for classifying if gaze was directed towards an object of interest. The algorithmic approach represents a viable and promising means for automating gaze classification for mobile eye tracking.

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  • (2024)Analyzing Reading Patterns with Webcams: An Eye-Tracking Study of the Albanian Language2024 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)10.23919/SoftCOM62040.2024.10721886(1-5)Online publication date: 26-Sep-2024
  • (2024)Eye-tracking research on teachers’ professional vision: A scoping reviewTeaching and Teacher Education10.1016/j.tate.2024.104568144(104568)Online publication date: Jul-2024
  1. Algorithmic gaze classification for mobile eye-tracking

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    cover image ACM Conferences
    ETRA '21 Adjunct: ACM Symposium on Eye Tracking Research and Applications
    May 2021
    78 pages
    ISBN:9781450383578
    DOI:10.1145/3450341
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 25 May 2021

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    Author Tags

    1. algorithmic eye-tracking
    2. computer vision
    3. image segmentation
    4. open source software

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    • (2024)Analyzing Reading Patterns with Webcams: An Eye-Tracking Study of the Albanian Language2024 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)10.23919/SoftCOM62040.2024.10721886(1-5)Online publication date: 26-Sep-2024
    • (2024)Eye-tracking research on teachers’ professional vision: A scoping reviewTeaching and Teacher Education10.1016/j.tate.2024.104568144(104568)Online publication date: Jul-2024

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