Drowsiness Estimation Based on Facial Near‐Infrared Images Using Sparse Coding-Reference-Cited by-同舟云学术

Drowsiness Estimation Based on Facial Near‐Infrared Images Using Sparse Coding

Published:2023-09-14 Issue:12 Volume:18 Page:1961-1963
ISSN:1931-4973
Container-title:IEEJ Transactions on Electrical and Electronic Engineering
language:en
Short-container-title:IEEJ Transactions Elec Engng

Author:

Okajima Tomoro¹,Yoshida Atsushi¹,Oiwa Kosuke²,Nagumo Kent¹,Nozawa Akio¹

Affiliation:

1. College of Science and Engineering, Aoyama Gakuin University, 5‐10‐1, Fuchinobe, Chuo Sagamihara Kanagawa 252‐5258 Japan

2. Department of Information and Management Systems Engineering, Nagaoka University of Technology, 1603‐1, Kamitomioka, Nagaoka Niigata 940‐2188 Japan

Abstract

Level 3 automated driving mandates the installation of a driver monitoring system that monitors the driver's condition, such as drowsiness. Conventional drowsiness detection has been hampered by the mental and physical burden of wearing equipment and the time required for detection. In this study, we applied sparse coding to facial images captured with near‐infrared light to extract features of facial skin blood flow information related to drowsiness and to estimate drowsiness. As a result, skin blood flow features related to drowsiness were extracted in the nasal area and other areas, and drowsiness was estimated with 74.6% accuracy. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Publisher

Wiley

Subject

Electrical and Electronic Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/tee.23913

Reference4 articles.

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3. Prediction of Automobile Driver Sleepiness. 1st Report. Rating of Sleepiness Based on Facial Expression and Examination of Effective Predictor Indexes of Sleepiness.

4. Spatial normalization of facial thermal images using facial landmarks

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