Detection of driver's drowsy facial expression

Taro Nakamura, Akinobu Maejima, Shigeo Morishima

Research output: Contribution to conferencePaperpeer-review

15 Citations (Scopus)


We propose a method for the estimation of the degree of a driver's drowsiness on basis of changes in facial expressions captured by an IR camera. Typically, drowsiness is accompanied by falling of eyelids. Therefore, most of the related studies have focused on tracking eyelid movement by monitoring facial feature points. However, textural changes that arise from frowning are also very important and sensitive features in the initial stage of drowsiness, and it is difficult to detect such changes solely using facial feature points. In this paper, we propose a more precise drowsiness-degree estimation method considering wrinkles change by calculating local edge intensity on faces that expresses drowsiness more directly in the initial stage.

Original languageEnglish
Number of pages5
Publication statusPublished - 2013 Jan 1
Event2013 2nd IAPR Asian Conference on Pattern Recognition, ACPR 2013 - Naha, Okinawa, Japan
Duration: 2013 Nov 52013 Nov 8


Conference2013 2nd IAPR Asian Conference on Pattern Recognition, ACPR 2013
CityNaha, Okinawa


  • Drowsiness level estimation
  • Edge intensity
  • Face texture analysis
  • K-NN
  • Wrinkles detection

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition


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