Lau, C. and Leong, H. and Chuah, Joonhuang and Kamarudin, N.H. (2021) An eye fatigue recognition system using YOLOv2. In: rd IEEE International Virtual Conference on Innovations in Power and Advanced Computing Technologies, i-PACT 2021, 27 November 2021, Virtual, Online.
Full text not available from this repository.Abstract
The rapid increase in global population significantly drives the hiking demand for transportations. This trend further leads to the increase in the number of road traffic accidents globally. Based on a study, fatigue due to prolonged driving is one of the leading causes for traffic accidents. With a customized Graphical User Interface (GUI), this work aims to develop an eye fatigue recognition system using YOLOv2 model. The proposed method used PERCLOS and blink rate parameters as indicators to determine the alertness of the user. This proposed method achieved a real-time average accuracy of 99.23 in normal lighting conditions and 98.57 in low light conditions. © 2021 IEEE.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Funders: | None |
| Uncontrolled Keywords: | Highway accidents, Blink rates; Driving alertness; Eye fatigue; Eye fatigue recognition; Global population; PERCLOS; Rate parameters; Recognition systems; Road traffic accidents; YOLOv2, Graphical user interfaces |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering > Department of Electrical Engineering |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 28 Oct 2024 03:03 |
| Last Modified: | 28 Oct 2024 03:03 |
| URI: | http://eprints.um.edu.my/id/eprint/36120 |
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