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Classification of Visual Attention Level During Target Gazing Using Microsaccades

  • Soichiro YokooEmail author
  • Nobuyuki Nishiuchi
  • Kimihiro Yamanaka
Conference paper
  • 45 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11960)

Abstract

In the previous researches on microsaccades, a typical and basic experimental method involves the following: a dot is displayed as a visual target in the middle or near the middle of a monitor, and eye movements of the subject are measured, and then the number of microsaccades is extracted from the measured eye movements. However, it is difficult to determine whether or not the subject is paying visual attention while gazing at the target, and the degree of visual attention paid by the subject. This paper proposes a system that uses microsaccades to classify visual attention levels during visual target gazing. In our experiment, ten subjects performed three tasks requiring different levels of visual attention. Microsaccades were measured and the number of microsaccades was extracted for each task. Statistical analysis showed that the number of microsaccades differed among the tasks. Our results suggest that visual attention level can be classified by the number of microsaccades.

Keywords

Microsaccade Visual attention Eye tracking 

Notes

Acknowledgements

We would like to thank Dr. Takao Fukui at Tokyo Metropolitan University for comments that greatly improved the manuscript.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2020

Authors and Affiliations

  • Soichiro Yokoo
    • 1
    Email author
  • Nobuyuki Nishiuchi
    • 1
  • Kimihiro Yamanaka
    • 2
  1. 1.Graduate School of Systems Design, Faculty of Computer ScienceTokyo Metropolitan UniversityHinoJapan
  2. 2.Graduate School of Natural Science, Faculty of Intelligence and InformaticsKonan UniversityKobeJapan

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