FPN-D-Based Driver Smoking Behavior Detection Method
Zuopeng Zhao, Haihan Zhao, Chen Ye, Xinzheng Xu, Kai Hao, Hualin Yan, Lan Zhang, Yi Xu · IETE Journal of Research · 2021
In view of the fact that a driver's smoking behavior seriously affects the driving safety, a feature pyramid network (FPN)-based smoking behavior identification method has been studied in order to reduce the occurrence of the driver smoking. Most of the existing research has been focused on detection and recognition based on movements while smoking or smog characteristics. Therefore, the probability of misjudgment in such methods is high, thus to address this issue, the present work proposes a method based on FPN to detect the driver's smoking behavior. FPN has been combined with the dilated convolution technique in order to detect a small target object in the driver's image and recognize their smoking behavior. By using the driver behavior images collected from the vehicle platform, a simulation experiment was carried out by employing the behavior identification method proposed in this work. The experimental results show that the accuracy of the proposed method is 94.75%, the recall rate is 96%, the precision rate is 95.05% and the area under the receiver operating characteristic curve is 95.5%.