Detection on safety helmet wearing of electrical bike riders

Journal Title: Nantong Daxue xuebao. Ziran kexue ban. - Year 2023, Vol 22, Issue 2

Abstract

To improve the safety helmet wearing rate of electrical bike(e-bike) riders, a safety helmet wearing behavior detection method based on deep learning was proposed. In order to solve the problem of small targets(distant ebikes), covered e-bikes and riders in video detection image which can easily lead to target loss when deep convolutional neural network performs detection task, the feature selection layer of feature graph in the backbone network was redesigned based on EfficientNet target detection framework. Pixel-level scaling(PLS) module was proposed to construct a new PLS-Det model for safety helmet wearing behavior detection, which can adapt to complex e-bike flow scenarios. Take typical urban roads in Nantong city, Jiangsu Province for example, the detection model was trained and optimized using the video image data of e-bike flow in different viewing angle, time periods and under different weather conditions(including 5 408 positive samples and 7 156 negative samples). The detection performances of EfficientDet-d0, EfficientDet-Optimize and PLS-Det models were compared with the results of ablation experiment and artificial detection. The experimental results show that the proposed PLS-Det model can significantly enrich the features of small targets and blocked targets by re-selecting feature layers and adding PLS module, while ensuring the stability of computational efficiency. The detection accuracy of this detection model is 95.8%, which can meet the accuracy requirements of safety helmet wearing behavior of e-bike riders.

Authors and Affiliations

ANG Tianpei;GONG Hao;LI Hongliang;CAO Yikai;LIAO Jiaqi;SHI Quan

Keywords

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  • EP ID EP719952
  • DOI 10.12194/j.ntu.20211231001
  • Views 53
  • Downloads 0

How To Cite

ANG Tianpei;GONG Hao;LI Hongliang;CAO Yikai;LIAO Jiaqi;SHI Quan (2023). Detection on safety helmet wearing of electrical bike riders. Nantong Daxue xuebao. Ziran kexue ban., 22(2), -. https://europub.co.uk/articles/-A-719952