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Driver fatigue detection based on eye tracking and dynamic template matching
Abstract
A vision-based real-time driver fatigue detection system is proposed for driving safely. The driver's face is located, from color images captured in a car, by using the characteristic of skin colors. Then, edge detection is used to locate the regions of eyes. In addition to being used as the dynamic templates for eye tracking in the next frame, the obtained eyes' images are also used for fatigue detection in order to generate some warning alarms for driving safety. The system is tested on a Pentium III 550 CPU with 128 MB RAM. The experiment results seem quite encouraging andpromising. The system can reach 20 frames per second for eye tracking, and the average correct rate for eye location and tracking can achieve 99.1% on four test videos. The correct rate for fatigue detection is l00%, but the average precision rate is 88.9% on the test videos.
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Cited by
In Ictu Oculi: Exposing AI Created Fake Videos by Detecting Eye Blinking
Li, Y., Chang, M.-C., & Lyu, S. (2018) · 2018 IEEE International Workshop on Information Forensics and Security (WIFS) · doi:10.1109/wifs.2018.8630787 · Cited by 1,089
A Survey on State-of-the-Art Drowsiness Detection Techniques
Ramzan, M., Khan, H. U., Awan, S. M., Ismail, A., Ilyas, M., & Mahmood, A. (2019) · IEEE Access · doi:10.1109/access.2019.2914373 · Cited by 361
Metadata
- Authors
- Horng, W.-B., Chen, C.-Y., Chang, Y., & Fan, C.-H.
- Venue
- IEEE International Conference on Networking, Sensing and Control, 2004
- Publisher
- IEEE
- Published
- 2004
- Pages
- 7-12
- OpenAlex
- W2105174503
- Cited by
- 229
- References
- 0
- FWCI
- 8.87
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Horng, W.-B., Chen, C.-Y., Chang, Y., & Fan, C.-H. (2004). Driver fatigue detection based on eye tracking and dynamic template matching. IEEE International Conference on Networking, Sensing and Control, 2004. https://doi.org/10.1109/icnsc.2004.1297400
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