The Assessment of Driver's Arousal States from the Classification of Eye-Blink Patterns

  • Authors:
  • Yoshihiro Noguchi;Keiji Shimada;Mieko Ohsuga;Yoshiyuki Kamakura;Yumiko Inoue

  • Affiliations:
  • Information Technology Lab., AsahiKASEI Corp., Kanagawa, Japan 243-0021;Information Technology Lab., AsahiKASEI Corp., Kanagawa, Japan 243-0021;Biomedical Engneering, Osaka Institute of Technology, Osaka, Japan 535-8585;Biomedical Engneering, Osaka Institute of Technology, Osaka, Japan 535-8585;Biomedical Engneering, Osaka Institute of Technology, Osaka, Japan 535-8585

  • Venue:
  • EPCE '09 Proceedings of the 8th International Conference on Engineering Psychology and Cognitive Ergonomics: Held as Part of HCI International 2009
  • Year:
  • 2009

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Abstract

To realize the real-time assessment of driver's arousal states, we propose the assessment method based on the analysis of eye-blink characteristics form image sequences. The driver's arousal level while driving is not monotonous falling from high to low. We proposed the two-dimensional arousal states transition model which was taken into account the fact that a driver usually held out against sleepiness. The eye-blink pattern categories were classified from image sequence using HMM (Hidden Markov Model), then the driver's arousal states were finally assessed using HMM by histogram distribution of those typical eye-blink categories. The arousal assessment results are also verified against the rating results by trained raters.