Motorcycle driving violation detection based on improved YOLOv8 and DeepSORT

Long Zhang; Wei Jia

doi:10.1117/12.3035396

19 July 2024 Motorcycle driving violation detection based on improved YOLOv8 and DeepSORT

Long Zhang, Wei Jia

Proceedings Volume 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024); 132132F (2024) https://doi.org/10.1117/12.3035396
Event: International Conference on Image Processing and Artificial Intelligence (ICIPAl2024), 2024, Suzhou, China

Abstract

Aiming at the problem that it is not easy to detect motorcycle driving violations on the road, a motorcycle violation detection method with improved YOLOv8 and DeepSORT is proposed. The method uses the YOLOv8 algorithm as a target detection model, introduces a global attention mechanism (GAM Attention) in the backbone network to refine the learning of key semantic information and improve the feature extraction capability of the network; adopts the WIOU (Wise-IoU) loss function to accelerate the convergence speed and improve the regression accuracy; and uses DeepSORT as a target tracking model. ShuffleNetv2, a lightweight network, is introduced as the appearance feature extraction network to reduce the parameters of the model and maintain good accuracy; re-training on the motorcycle reidentification dataset improves the identity switching problem of the motorcycle target in the occlusion scenario. Finally, the tracked motorcycle targets are detected for driving violations. The experimental results show that compared with YOLOv8, the motorcycle and helmet detection accuracies are improved, reaching 98.2% and 98.6%, respectively; the size of the DeepSORT tracking model is reduced by 82%, which enhances the model's portability; and the algorithm has strong robustness in different traffic scenarios. Finally, the motorcycle target's driver and passenger did not wear a safety helmet, adding a parasol, and overloading three driving violations were detected, and the recognition rate reached 98.8%, 100%, and 98.5%, respectively, indicating that the method has some practical value.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Long Zhang and Wei Jia "Motorcycle driving violation detection based on improved YOLOv8 and DeepSORT", Proc. SPIE 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024), 132132F (19 July 2024); https://doi.org/10.1117/12.3035396

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KEYWORDS

Target detection

Detection and tracking algorithms

Feature extraction

Video

Target recognition

Data modeling

Education and training

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