University of Twente Student Theses
Development of a computer vision-based system for recognising fatigue of truck drivers.
Sowa, A.M. (2022) Development of a computer vision-based system for recognising fatigue of truck drivers.
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| Abstract: | Fatigue is inextricable from the environment of truck drivers. Despite the advances in fatigue detection systems, fatigue continues to be one of the leading causes of traffic accidents. Introducing a computer vision-based system for fatigue detection could divert that trend. This graduation project re-searched various computer vision techniques and facial-related fatigue parameters to develop such a system. Through the course of this research combination of yawning, head nodding, and OpenFace 2 as software is examined in detail, and finally, a system is proposed to detect the yawning and fatigue state of the driver. The machine learning algorithm used to determine the yawning state of a face given val-ues obtained from Facial Action Units has the accuracy of 0.961, recall of 0.899 and precision of 0.651. A low precision score is partially corrected by introducing various mitigation approaches. Subsequently, a fuzzy logic model based on yawning and head-nodding frequency is proposed as a model to deter-mine driver’s fatigue. |
| Item Type: | Essay (Bachelor) |
| Clients: | Techspread |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 50 technical science in general, 54 computer science |
| Programme: | Creative Technology BSc (50447) |
| Link to this item: | https://purl.utwente.nl/essays/92474 |
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