Driver Drowsiness Detection by Multi-task and Transfer Learning

Yuan Chang*, Wataru Kameyama

*この研究の対応する著者

研究成果: Conference contribution

抄録

In this busy modern society, there are many external and psychological factors that can cause people to feel tired. The severity of fatigue driving is comparable to drunk driving when we consider the accident rate. Therefore, how to avoid this situation has become an important issue. With the trend of machine learning becoming more mature, facial expression recognition has been widely used in real life. A large number of studies and reports about fatigue driving detection and how to improve fatigue driving can be found. Most of them either detect drowsiness states without detailed facial expressions or just look at a single part of face such as eye or mouth. However, we consider that each facial feature is highly correlated. For example, when a driver gets tired, his/her mouth and eyes are thought to change the states together. Thus, it is important to evaluate more than one facial feature at a time. Therefore, in this paper, we propose a new driver-drowsiness detection method by using multi-task and transfer learning. The proposed method first captures the drivers’ facial areas frame-by-frame in videos, and learns different facial features synchronously. The experimental results show that the proposal outperforms the ever-proposed methods on four scenarios out of the five and on the average in the NTHU driver drowsiness detection video dataset.

本文言語English
ホスト出版物のタイトルInternational Workshop on Advanced Imaging Technology, IWAIT 2022
編集者Masayuki Nakajima, Shogo Muramatsu, Jae-Gon Kim, Jing-Ming Guo, Qian Kemao
出版社SPIE
ISBN(電子版)9781510653313
DOI
出版ステータスPublished - 2022
イベント2022 International Workshop on Advanced Imaging Technology, IWAIT 2022 - Hong Kong, China
継続期間: 2022 1月 42022 1月 6

出版物シリーズ

名前Proceedings of SPIE - The International Society for Optical Engineering
12177
ISSN(印刷版)0277-786X
ISSN(電子版)1996-756X

Conference

Conference2022 International Workshop on Advanced Imaging Technology, IWAIT 2022
国/地域China
CityHong Kong
Period22/1/422/1/6

ASJC Scopus subject areas

  • 電子材料、光学材料、および磁性材料
  • 凝縮系物理学
  • コンピュータ サイエンスの応用
  • 応用数学
  • 電子工学および電気工学

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