Classification of gaze preference decision for human-machine interaction using eye tracking device

Sota Shimizu, Yoshiaki Tanzawa, Takumi Hashizume

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


This paper aims at classifying a gaze preference decision made taking individual difference into account. A proposed method focuses on a likelihood of a chosen face to the subject’s eye movement data measured by an eye tracking device and classifies the decision using an inferential statistical theory. A system is designed as changing displayed visual stimuli flexibly using the measured eye movement data as an image switcher. In order to discuss the proposed method, experiments using the image switcher are done. Two conditions are compared in experiments, i.e., one is when two faces are displayed side by side statically, and the other is when the face the subject tries to look at disappears dynamically. Thus, the proposed classification method is enhanced by discussing interesting results of the visual-psychophysical experiments, to supplement and progress the gaze cascade effect, which is a well known hypothesis of a psychophysical experiment.

Original languageEnglish
Pages (from-to)75-82
Number of pages8
JournalInternational Journal of Mechatronics and Automation
Issue number2
Publication statusPublished - 2012 Jan 1
Externally publishedYes


  • classification
  • eye-tracking device
  • gaze preference decision-making
  • image switcher
  • inferential statistics
  • visual-psychophysics, gaze cascade effect

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computational Mechanics
  • Industrial and Manufacturing Engineering
  • Computational Mathematics
  • Artificial Intelligence
  • Electrical and Electronic Engineering


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