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2020 | OriginalPaper | Chapter

Classification of Visual Attention Level During Target Gazing Using Microsaccades

Authors : Soichiro Yokoo, Nobuyuki Nishiuchi, Kimihiro Yamanaka

Published in: Transactions on Computational Science XXXV

Publisher: Springer Berlin Heidelberg

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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.

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next chapter Multiscale Analysis of Textual Content Using Eyegaze
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Metadata
Title
Classification of Visual Attention Level During Target Gazing Using Microsaccades
Authors
Soichiro Yokoo
Nobuyuki Nishiuchi
Kimihiro Yamanaka
Copyright Year
2020
Publisher
Springer Berlin Heidelberg
Book
Transactions on Computational Science XXXV

Print ISBN: 978-3-662-61091-6

Electronic ISBN: 978-3-662-61092-3

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-662-61092-3_1

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