期刊论文

Liu, HL

英文

Sensors

1424-3210

2024

24

2

636-

10.3390/s24020636

Conceptualization, H.L. and W.X.; methodology, W.X.; software, Z.M.; validation, W.C., W.X., and J.H.; formal analysis, W.C.; investigation, H.L.; resources, H.L.; data curation, W.C.; writing—original draft preparation, W.X.; writing—review and editing, W.X.; visualization, W.C.; supervision, H.L.; project administration, H.L.; funding acquisition, H.L. and Z.M. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Natural Science Foundation of China with Grant Nos. 61971182 and 62173133.

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Fatigue driving is a serious threat to road safety, which is why accurately identifying fatigue driving behavior and warning drivers in time are of great significance in improving traffic safety. However, accurately recognizing fatigue driving is still challenging due to large intra-class variations in facial expression, continuity of behaviors, and illumination conditions. A fatigue driving recognition method based on feature parameter images and a residual Swin Transformer is proposed in this paper. First, the face region is detected through spatial pyramid pooling and a multi-scale feature ...