A multi-feature fusion algorithm for driver fatigue detection based on a lightweight convolutional neural network

• Published in: The Visual computer Vol. 40; no. 4; pp. 2419 - 2441
• Main Authors: Cheng, Wangfeng, Wang, Xuanyao, Mao, Bangguo
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2024; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Artificial neural networks; Computer Graphics; Computer Science; Driver fatigue; Fatigue; Heart rate; Image Processing and Computer Vision; Lane changing; Lightweight; Mouth; Neural networks; Original Article; Physiology; Roads & highways; Sensors; Traffic; Vehicles; Warning systems; Fatigue detection; Multi-feature fusion; Pre-warning system; Lightweight convolutional neural network

The majority of the current widely used algorithms for fatigue detection rely on shallow learning to extract fatigue characteristics and use a single feature to determine the level of fatigue. The accuracy of detection is greatly affected by individual and environmental differences, and there are ce...