Driver drowsiness detection using facial thermal imaging in a driving simulator

Abstract

Driver drowsiness causes fatal driving accidents. Thermal imaging is a suitable drowsiness detection method as it is non-invasive and robust against changes in the ambient light. In this paper, driver drowsiness is detected by measuring the forehead temperature at the region covering the supratrochlear artery and also the cheek temperature. About 30 subjects drove on a highway in a driving simulator in two sessions. A thermal camera was used to monitor the facial temperature pattern. The subjects’ drowsiness levels were estimated by three human observers. The forehead and the cheek regions were located and tracked in each frame. The forehead and the cheek skin temperatures were obtained at three levels of drowsiness. The Support Vector Machine, the K-Nearest Neighbor, and the regression tree classifiers were used. From wakefulness to extreme drowsiness, the forehead skin temperature and the absolute cheek-forehead skin temperature gradient decreased by 0.46°C and 0.81°C, respectively. But the cheek skin temperature increased by 0.35°C in two sessions. The gradient difference is on average 50% higher than the forehead or the cheek temperature change alone. The results indicate that drowsiness can be detected with an accuracy of 82%, sensitivity of 85%, specificity of 90%, and precision of 84%. Driver drowsiness can be detected by monitoring changes in the forehead and the cheek temperature signal. Also, the temperature gradient can be used as a more robust and sensitive indicator of drowsiness.

Classification of User Emotional Experiences on B2C Websites Utilizing Infrared Thermal Imaging

“…There have been many studies using SVM models to classify emotions in thermal images [ 57 , 58 ]. An SVM model was chosen for the classification of emotional experiences, and this research was based on cross-subject training.…”

Trends and Future Prospects of the Drowsiness Detection and Estimation Technology

“…Similarly, Tashakori et al conducted a study using temperature information [ 63 ]. They detected driver drowsiness by measuring the forehead and cheek temperatures.…”

Evaluation of Driver Irritation using Deep Body Temperature Variability Analysis

“…Assessment of driver irritation is an important aspect that affects traffic safety and driving performance. Although continuous measurement of facial images and autonomic indices estimated from heartbeats [1][2][3][4][5] are used in automotive biometric measurements, these methods have drawbacks such as difficulty in privacy and noise removal. Therefore, in this study, we investigated the usefulness of continuous tympanic temperature measurement from its time-series data using deep body temperature variation analysis on a trial basis, and also verified whether it is possible to objectively evaluate driver irritation.…”