@Article{cmc.2020.09763,
AUTHOR = {Yuyang Sun, Peizhou Yan, Zhengzheng Li, Jiancheng Zou, Don Hong},
TITLE = {Driver Fatigue Detection System Based on Colored and Infrared  Eye Features Fusion},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {63},
YEAR = {2020},
NUMBER = {3},
PAGES = {1563--1574},
URL = {http://www.techscience.com/cmc/v63n3/38893},
ISSN = {1546-2226},
ABSTRACT = {Real-time detection of driver fatigue status is of great significance for road 
traffic safety. In this paper, a proposed novel driver fatigue detection method is able to 
detect the driver’s fatigue status around the clock. The driver’s face images were captured 
by a camera with a colored lens and an infrared lens mounted above the dashboard. The 
landmarks of the driver’s face were labeled and the eye-area wassegmented. By calculating 
the aspect ratios of the eyes, the duration of eye closure, frequency of blinks and PERCLOS 
of both colored and infrared, fatigue can be detected. Based on the change of light intensity 
detected by a photosensitive device, the weight matrix of the colored features and the 
infrared features was adjusted adaptively to reduce the impact of lighting on fatigue 
detection. Video samples of the driver’s face were recorded in the test vehicle. After 
training the classification model, the results showed that our method has high accuracy on 
driver fatigue detection in both daytime and nighttime.},
DOI = {10.32604/cmc.2020.09763}
}