Paper
27 June 2023 A fatigue driving detection algorithm based YOLOv5
Zhanli Li, Ni Jia, Hongmei Jin
Author Affiliations +
Proceedings Volume 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022); 127052N (2023) https://doi.org/10.1117/12.2679987
Event: Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 2022, Nanjing, China
Abstract
Aiming at the problems of slow detection speed and low detection accuracy in existing fatigue driving detection algorithms, a fatigue driving detection algorithm based on YOLOv5 is proposed. In order to improve the feature extraction ability of the network, the convolution module is used to replace the slice structure in Backbone; the algorithm combines the data features of fatigue driving images to simplify and optimize the Neck structure of the YOLOv5 model, which will be suitable for detecting 19×19 features of larger size objects. Graph branch pruning to reduce model complexity and improve real-time detection. Finally, on the basis of facial feature extraction, the algorithm determines the state of fatigue features according to PERCLOS and POM parameters combined with thresholds and outputs the results. The experimental results on the NHTU-DDD data set show that the accuracy of the detection model reaches 95.25%, the model size is only 10MB, and the single-frame detection speed is 9ms, which is 21.5% higher than the original YOLOv5 algorithm. At the same time, the model parameters are greatly reduced, which can better meet the real-time requirements of fatigue detection application scenarios.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhanli Li, Ni Jia, and Hongmei Jin "A fatigue driving detection algorithm based YOLOv5", Proc. SPIE 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 127052N (27 June 2023); https://doi.org/10.1117/12.2679987
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KEYWORDS
Material fatigue

Data modeling

Mouth

Detection and tracking algorithms

Feature extraction

Performance modeling

Eye models

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