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Saccade Direction Information Channel

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Neural Information Processing (ICONIP 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13623))

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Abstract

Eye tracking has become an increasingly important technology in many fields of research, such as marketing, human computer interaction, psychology, and also in human cognition. Understanding the human eye movements, while viewing specific scenarios, can be of great support for improving visual stimuli. However, the challenging problem with this kind of spatio-temporal data is to find quantitative links between eye movements and human cognition. This paper introduces the information channel based on saccade direction. The gaze transition between different saccade directions is modeled as a discrete information channel, which we call saccade direction information channel. The channel is applied to an eye-tracking dataset on Van Gogh’s paintings observation. In our results, horizontal saccades are more frequent than vertical saccades, and the information conveyed in horizontal/vertical displacements, measured as the mutual information of the channel, is higher than in diagonal displacements. By comparing the results to our previous spatial gaze channel between Areas of Interest (AOIs) we constate that the spatial channel discriminates better between the observed images, while the direction channel discriminates better between observers.

Supported by the National Natural Science Foundation of China under grant No. 61702359, and by Grant PID2019-106426RB-C31 funded by MCIN/AEI/10.13039/501100011033.

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Author information

Authors and Affiliations

  1. College of Intelligence and Computing, Tianjin University, Tianjin, 300350, China

    Qiaohong Hao, Yi Zhang & Jiawan Zhang

  2. Institute of Informatics and Applications, University of Girona, Girona, 17003, Spain

    Mateu Sbert, Miquel Feixas & Marius Vila

Authors
  1. Qiaohong Hao
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  2. Mateu Sbert
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  3. Miquel Feixas
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  4. Yi Zhang
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  5. Marius Vila
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  6. Jiawan Zhang
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Corresponding authors

Correspondence to Mateu Sbert or Jiawan Zhang .

Editor information

Editors and Affiliations

  1. Indian Institute of Technology Indore, Indore, India

    Mohammad Tanveer

  2. Indian Institute of Information Technology - Allahabad, Prayagraj, India

    Sonali Agarwal

  3. Kobe University, Kobe, Japan

    Seiichi Ozawa

  4. Indian Institute of Technology Patna, Patna, India

    Asif Ekbal

  5. University of Innsbruck, Innsbruck, Austria

    Adam Jatowt

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Hao, Q., Sbert, M., Feixas, M., Zhang, Y., Vila, M., Zhang, J. (2023). Saccade Direction Information Channel. In: Tanveer, M., Agarwal, S., Ozawa, S., Ekbal, A., Jatowt, A. (eds) Neural Information Processing. ICONIP 2022. Lecture Notes in Computer Science, vol 13623. Springer, Cham. https://doi.org/10.1007/978-3-031-30105-6_4

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  • DOI: https://doi.org/10.1007/978-3-031-30105-6_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-30104-9

  • Online ISBN: 978-3-031-30105-6

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