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Road rage detection algorithm based on fatigue driving and facial feature point location

  • S.I: Machine Learning based semantic representation and analytics for multimedia application
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Abstract

In order to monitor whether a driver is tired or prone to road rage in real time and avoid some traffic accidents, a real-time detection method of driver's facial expression based on the facial feature point location is proposed. First, we use the AdaBoost face detection algorithm based on Haar characteristics to detect the presence of a face and use the face feature point localization algorithm to obtain the required face feature points. Then, the value of eye aspect ratio is calculated according to the feature point data of the face-eye region, which indicates the opening degree of eyes. The driver is detected whether he (she) is in fatigue driving according to the appropriate threshold. We improve the detection method of fatigue driving and apply it to the road rage detection algorithm. We first propose the ratios of the brow-eye distance and mouth closure (RBEM) as indicators to determine whether the driver has road rage characteristics. Experimental results verify the effectiveness of the method.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (No.61966013), Hainan Natural Science Foundation of China (No.620RC602, 618MS056), National Natural Science Foundation of China (No.6176050136) and Key Laboratory of Data Science and Smart Education. Shulei Wu and Huandong Chen are the corresponding authors.

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Authors and Affiliations

  1. School of Information Science and Technology, Hainan Normal University, Haikou, 571158, China

    Wu Shulei, Suo Zihang, Chen Huandong & Zhao Yuchen

  2. School of Mathematics and Statistics, Hainan Normal University, Haikou, 571158, China

    Zhang Yang

  3. Smart Police College, People’s Police University of China, Langfang, 065000, China

    Chen Jinbiao

  4. School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China

    Meng Qiaona

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  1. Wu Shulei
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  2. Suo Zihang
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  3. Chen Huandong
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  4. Zhao Yuchen
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  5. Zhang Yang
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  6. Chen Jinbiao
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  7. Meng Qiaona
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Correspondence to Wu Shulei or Chen Huandong.

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Shulei, W., Zihang, S., Huandong, C. et al. Road rage detection algorithm based on fatigue driving and facial feature point location. Neural Comput & Applic 34, 12361–12371 (2022). https://doi.org/10.1007/s00521-021-06856-0

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