Ming-da SONG
ABSTRACT
For some large and complex operating platforms in machinery factories, in order to detect fatigued workers in time, machine vision is adopted for fatigue detection. Normal camera cannot cover the entire working range. So come up with an idea to use an industrial computer to control the pan-tilt for face tracking and fatigue detection. First, face detection is performed on the image information captured by the pan-tilt. Then, the pan-tilt is controlled to rotate according to the position of the face to achieve the purpose of tracking the face of the staff in real time. On this basis, the feature points recognized by face detection algorithm and the PERCLOS algorithm are used to calculate, The thresholds of EAR value and MAR value were set as 0.18 and 0.4 respectively according to the experimental results to identify the fatigue features of the face for fatigue detection. Finally, whether the person is in a state of fatigue is judged according to whether the percentage of the time that the person is in a fatigue characteristic exceeds 75% .The results show that the corresponding hardware equipment and the algorithm used can make the recognition accuracy basically reach 90% during working time, and the detection time is less than 90ms, which satisfy the requirements of real-time face tracking and fatigue detection accuracy and execution efficiency under working state.
- XIANG Yue. Research on the fatigue detection methods of air traffic controller and application system design based on cognitive science .D. Civil Aviation Flight University of China,2019.Google Scholar
- LIANG Lu-hong, AI Haizhou, XU Guang-you, A Survey of human face detection .J. Chinese Journal of Computers (May 2002),449-458 pages. DOI: https://doi.org/10.3321/j.issn:0254-4164.2002.05.001Google Scholar
- Andre sobiecki, Gilson antonio giraldi, Luiz antonio pereira neves, An Automatic Framework for Segmentation and Digital Inpainting of 2d Frontal Face Images .J. IEEE Latin America Transactions, 2012, 10(6). DOI: https://doi.org/10.1109/TLA.2012.6418131Google Scholar
- XU Yan, WANG Wei-lan. Research on Face Detection Technology Based on Vision Motion .J. Computer Simulation, 2014, 31(1): 434-437. DOI: https://doi.org/10.3969/j.issn.1006-9348.2014.01.098Google Scholar
- Bacha rehman, Wee hong ong, Abby chee hong tan, Face Detection and Tracking Using Hybrid Margin-based Roi Techniques .J. The Visual Computer, 2020, 36(3). DOI: https://doi.org/10.1007/s00371-019-01649-yGoogle Scholar
- Mandal B, Li L, Wang G, Towards Detection of Bus Driver Fatigue Based on Robust Visual Analysis of Eye State .J. IEEE Transactions on Intelligent Transportation Systems, 2017, 18(3): 545-557. DOI:https://doi.org/10.1109/TITS.2016.2582900Google ScholarDigital Library
- SUN Zhi. The Research and Implementation of Face Recognition Experimental Platform based on OpenCV .D. JILIN UNIVERSITY. 2014. DOI:https://doi.org/ 10.7666/d.D661714Google Scholar
- YANG Yang. Design of movement vision tracking system based on specific feature identification .J. Modern Electronics Technique, 2017, 40(2): 94-98. DOI:https://doi.org/10.16652/j.issn.1004-373x.2017.02.022Google Scholar
- ZHANG Xu-xin, WANG Xue-song, MA Yong, International Research Progress on Driving Behavior and Driving Risks.J. China Journal of Highway and Transport, 2020, 33(6): 1-17. DOI:https://doi.org/10.3969/j.issn.1001-7372.2020.06.001Google Scholar
- Gabriel soares, Danilo de lima, Arthur miranda neto. A Mobile Application for Driver's Drowsiness Monitoring Based on Perclos Estimation .J. IEEE Latin America Transactions, 2019, 17(2). DOI:https://doi.org/10.1109/TLA.2019.8863164Google Scholar
- Kumar A, Kumar M, Kaur A, Face Detection in Still Images Under Occlusion and Non-uniform Illumination .J. Multimedia Tools and Applications, 2021, 80(10): 14565-14590. DOI:https://doi.org/10.1007/s11042-020-10457-9Google ScholarDigital Library
- WANG Lei, SUN Rui-shan. Study on Face Feature Recognition-based Fatigue Monitoring Method for Air Traffic Controller .J. China Safety Science Journal, 2012, 22(7): 66-71. DOI:https://doi.org/10.3969/j.issn.1003-3033.2012.07.011Google Scholar
- HUANG Xiu-qing, HUANG Wei, GAO Qiang, Algorithm of Estimating Inner Lip Opening Distance Based on Classification of Mouth States .J. Computer Science, 2014, 41(5): 296-298, 303. DOI:https://doi.org/10.3969/j.issn.1002-37X.2014.05.063Google Scholar
- Gallup andrew c, Church allyson m, Pelegrino anthony j. Yawn Duration Predicts Brain Weight and Cortical Neuron Number in Mammals .J. Biology Letters, 2016, 12(10). DOI:https://doi.org/10.1098/rsbl.2016.0545Google Scholar
- Alioua N,Amine A,Rziza M. Driver's Fatigue Detection Based on Yawning Extraction .J. International Journal of Vehicular Technology, 2014, 2014: 47-75. DOI:https://doi.org/10.1155/2014/678786Google Scholar
Index Terms
- Detection of Fatigued Face
Recommendations
Adaptive appearance model tracking for still-to-video face recognition
Systems for still-to-video face recognition (FR) seek to detect the presence of target individuals based on reference facial still images or mug-shots. These systems encounter several challenges in video surveillance applications due to variations in ...
Tracking a detected face with dynamic programming
In this paper, we consider the problem of tracking a moving human face in front of a video camera in real-time for a model-based coding application. The 3D head tracking in a MBC system could be implemented sequentially as 2D location tracking, coarse ...
Pose-Robust Facial Expression Recognition Using View-Based 2D + 3D AAM
This paper proposes a pose-robust face tracking and facial expression recognition method using a view-based 2D 3D active appearance model (AAM) that extends the 2D 3D AAM to the view-based approach, where one independent face model is used for a ...
Comments