Fatigue driving and distraction detection system based on machine vision
DOI: 10.23977/acss.2022.060303 | Downloads: 39 | Views: 907
Author(s)
Hongzhao Chen 1, Ziyi Luo 1, Yuxuan Feng 1, Xiaoyang Wang 1, Chunyou Lin 1
Affiliation(s)
1 Dongguan University of Technology, Dongguan 523000, Guangdong Province, China
Corresponding Author
Chunyou LinABSTRACT
The development of automobiles has brought great convenience to people's travel. However, the rapid increase in the number of vehicles leads to the increase of traffic accidents. Fatigue and distracted driving has become the important factor causing traffic accidents, and the detection of fatigue driving technology has gradually attracted the attention of researchers. In order to cope with different road conditions and complex in-vehicle environments, methods based on multi sensor have become the mainstream for application to driving detection, however, different driving habits and environments may lead to false information. In this paper, we propose an integrated-information method based on machine vision and deep learning, the Dlib library with 68 features is used to map the face, PERCLOS method is used to calculate the EAR (eye aspect ratio) and MAR (mouth aspect ratio) to evaluate the fatigue level of the face, also, we turn the key points of the 2D face into the 3D face model, and calculate the Euler angle of the head position in real time. A Yolov5 target-detected algorithm is used to identify and warn distracted behaviors such as smoking, drinking, and using mobile phones. The training accuracy reaches 90.23%, and the total detection frame rate is 4.78 frames per second. In our system, a UI is designed based on Wxpython, and thresholds such as eyes-closed and mouth-closed behaviors could be set in real time through a human-computer interface, the mode of monitoring behavior could be switched and the abnormal driving data will be recorded at the same time. The detection system designed in this paper is mainly divided into three parts: facial feature detection, head position prediction, distracted behaviors detection which realizes the evaluation and warning of the driver's fatigue driving and distracted state.
KEYWORDS
Fatigue driving, deep learning, face detection, target detectionCITE THIS PAPER
Hongzhao Chen, Ziyi Luo, Yuxuan Feng, Xiaoyang Wang, Chunyou Lin, Fatigue driving and distraction detection system based on machine vision. Advances in Computer, Signals and Systems (2022) Vol. 6: 19-25. DOI: http://dx.doi.org/10.23977/acss.2022.060303.
REFERENCES
[1] Li Duhou, Liu Qun, Yuan Wei et al.Relationship between fatigue driving and traffic accidents [J]. Journal of Transportation Engineering, 2010 (4): 104109.
[2] Shuang Shuang Lv. Review of patented techniques of fatigue driving based on image analysis [J]. China Science and Technology Information 2018 (17): 17-19.
[3] Lizhen Xu. Research on fatigue driving detection technology [J]. The Internet of Things Tech, 2017, 7(04):95-96+98. DOI:10.16667/j.issn.2095-1302.2017.04.031.
[4] Fu R, Wang H, Zhao W. Dynamic driver fatigue detection using hidden Markov model in real driving condition[J]. Expert Systems with Applications, 2016, 63: 397-411.
[5] Sangeetha M, Kalpanadevi S. Driver Fatigue Management System using Embedded ECG Sensor[J]. International Journal for Scientific Research & Development, 2015(4): 1220-1224.
[6] Jian W, Bing L. Design and Simulated Implementation of MATLAB-Based Warning System for Fatigue Driving Driver[C]// Ninth International Conference on Hybrid Intelligent Systems. IEEE, 2009:467-470.
[7] X.-Y. Gao, Y.-F. Zhang, W.-L. Zheng, et al., Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference on (IEEE, 2015), 767–770 (2015)
[8] LEE K, HYUN S A E, OAH S. Detecting driver fatigue by steering wheel grip force[J]. International Journal of Contents, 2016, 12(1): 44-48.
[9] T Soukupova´, Ech J C. Real-Time Eye Blink Detection using Facial Landmarks. 2016.
[10] M. Mao, L. Du, Vehicular Electronics and Safety, 2007. ICVES. IEEE International Conference on (IEEE, 2007), 1–4 (2007).
Downloads: | 16043 |
---|---|
Visits: | 271496 |
Sponsors, Associates, and Links
-
Power Systems Computation
-
Internet of Things (IoT) and Engineering Applications
-
Computing, Performance and Communication Systems
-
Journal of Artificial Intelligence Practice
-
Journal of Network Computing and Applications
-
Journal of Web Systems and Applications
-
Journal of Electrotechnology, Electrical Engineering and Management
-
Journal of Wireless Sensors and Sensor Networks
-
Journal of Image Processing Theory and Applications
-
Mobile Computing and Networking
-
Vehicle Power and Propulsion
-
Frontiers in Computer Vision and Pattern Recognition
-
Knowledge Discovery and Data Mining Letters
-
Big Data Analysis and Cloud Computing
-
Electrical Insulation and Dielectrics
-
Crypto and Information Security
-
Journal of Neural Information Processing
-
Collaborative and Social Computing
-
International Journal of Network and Communication Technology
-
File and Storage Technologies
-
Frontiers in Genetic and Evolutionary Computation
-
Optical Network Design and Modeling
-
Journal of Virtual Reality and Artificial Intelligence
-
Natural Language Processing and Speech Recognition
-
Journal of High-Voltage
-
Programming Languages and Operating Systems
-
Visual Communications and Image Processing
-
Journal of Systems Analysis and Integration
-
Knowledge Representation and Automated Reasoning
-
Review of Information Display Techniques
-
Data and Knowledge Engineering
-
Journal of Database Systems
-
Journal of Cluster and Grid Computing
-
Cloud and Service-Oriented Computing
-
Journal of Networking, Architecture and Storage
-
Journal of Software Engineering and Metrics
-
Visualization Techniques
-
Journal of Parallel and Distributed Processing
-
Journal of Modeling, Analysis and Simulation
-
Journal of Privacy, Trust and Security
-
Journal of Cognitive Informatics and Cognitive Computing
-
Lecture Notes on Wireless Networks and Communications
-
International Journal of Computer and Communications Security
-
Journal of Multimedia Techniques
-
Automation and Machine Learning
-
Computational Linguistics Letters
-
Journal of Computer Architecture and Design
-
Journal of Ubiquitous and Future Networks