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The Euro-China Conference on Intelligent Data Analysis and Applications

ECC 2018: Proceedings of the Fifth Euro-China Conference on Intelligent Data Analysis and Applications pp 491–498Cite as

Fatigue Driving Detection and Warning Based on Eye Features

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 891))

Abstract

For the aim of reducing the occurrence of traffic accidents caused by fatigue driving, it is of great significance to design a system based on eye features for fatigue driving detection and early warning. The system uses a camera to capture images, using an improved Haar feature cascade classification algorithm to detect the face area, and then uses a Ensemble of Regression Trees (ERT) cascade regression algorithm to detect human eyes and mark 12 points in the area. According to the Eye Aspect Ratio (EAR) algorithm and the blink frequency, the driver’s fatigue state can be determined and the alarm can be timely issued,and the image will be uploaded to the cloud platform of the Internet of things.

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References

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Acknowledgments

This research was supported in part by grants from the International Cooperation and Exchange Program of Shaanxi Province (2018KW-026), Natural Science Foundation of Shaanxi Province (2018JM6120), Xi’an Science and Technology Plan Project (201805040YD18CG24(6)), Major Science and Technology Projects of XianYang City (2017k01-25-12), Graduate Innovation Fund of Xi’an University of Posts & Telecommunications (CXJJ2017012, CXJJ2017028, CXJJ2017056).

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Authors and Affiliations

  1. School of Communication and Engineering, Xi’an University of Post and Telecommunications, Xi’an, 710121, China

    Zhiwei Zhang, Ruijun Zhang & Jianguo Hao

  2. School of Automation, Xi’an University of Posts and Telecommunications, Xi’an, 710121, China

    Junsuo Qu

Authors
  1. Zhiwei Zhang
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  2. Ruijun Zhang
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  3. Jianguo Hao
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  4. Junsuo Qu
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Corresponding author

Correspondence to Zhiwei Zhang .

Editor information

Editors and Affiliations

  1. Department of Computer Science, VSB-Technical University of Ostrava, Ostrava, Czech Republic

    Pavel Krömer

  2. School of Automation, Xi’an University of Posts and Telecommunications, Xi’an, China

    Hong Zhang

  3. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China

    Yongquan Liang

  4. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

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Zhang, Z., Zhang, R., Hao, J., Qu, J. (2019). Fatigue Driving Detection and Warning Based on Eye Features. In: Krömer, P., Zhang, H., Liang, Y., Pan, JS. (eds) Proceedings of the Fifth Euro-China Conference on Intelligent Data Analysis and Applications. ECC 2018. Advances in Intelligent Systems and Computing, vol 891. Springer, Cham. https://doi.org/10.1007/978-3-030-03766-6_55

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