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Implicit calibration using predicted gaze targets

Published:14 March 2016Publication History

ABSTRACT

The paper presents the algorithm supporting an implicit calibration of eye movement recordings. The algorithm does not require any explicit cooperation from users, yet it uses only information about a stimulus and an uncalibrated eye tracker output. On the basis of this data, probable fixation locations are calculated at first. Such a fixation set is used as an input to the genetic algorithm which task is to choose the most probable targets. Both information can serve to calibrate an eye tracker. The main advantage of the algorithm is that it is general enough to be used for almost any stimulation. It was confirmed by results obtained for a very dynamic stimulation which was a shooting game. Using the calibration function built by the algorithm it was possible to predict where a user will click with a mouse. The accuracy of the prediction was about 75%.

References

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    • Published in

      cover image ACM Conferences
      ETRA '16: Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications
      March 2016
      378 pages
      ISBN:9781450341257
      DOI:10.1145/2857491

      Copyright © 2016 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 14 March 2016

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      Overall Acceptance Rate69of137submissions,50%

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      ETRA '24
      The 2024 Symposium on Eye Tracking Research and Applications
      June 4 - 7, 2024
      Glasgow , United Kingdom

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