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Blink Detection Using Image Processing to Predict Eye Fatigue

  • Akihiro KuwaharaEmail author
  • Rin Hirakawa
  • Hideki Kawano
  • Kenichi Nakashi
  • Yoshihisa Nakatoh
Conference paper
  • 303 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1253)

Abstract

With the use of information terminals represented by smartphones, our eyes get tired. One index indicating eye fatigue is a change in the number of blinks. In this study, we set the ultimate goal that is to develop eye fatigue prevention system with less time and less physical burden for patient. By doing this, the information terminal performs a flickering of the eyes using a detection camera and a validity check. Previous EAR study with blink detection is confirmed to be effective, and this paper proposes a new formula EARM used EAR. As an evaluation method of blink detection, we used the total time average of the square of the residual value. The results showed that EARM was more accurate than the EAR. Further, it was suggested that the number of blinks during VDT work can be classified into several patterns.

Keywords

Eye fatigue Image processing Dlib EAR 

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  • Akihiro Kuwahara
    • 1
    Email author
  • Rin Hirakawa
    • 1
  • Hideki Kawano
    • 1
  • Kenichi Nakashi
    • 1
  • Yoshihisa Nakatoh
    • 1
  1. 1.Kyushu Institute of TechnologyKitakyushu-shiJapan

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