Algorithm for Detecting Abnormal Pedestrian Behavior on Escalators Based on Improved YOLOv8
Most of the safety hazards for escalator passengers result from abnormal behaviors of the passengers.This paper proposes an escalator passenger anomaly detection algorithm DEW-YOLOv8 based on the improved YOLOv8.Firstly,to enhance the detection efficiency of the al-gorithm,the standard convolution module in the C2f module of YOLOv8 is replaced by the more efficient DSConv module to form the C2f_DSConv module.Secondly,to address the issue of easy missed detections caused by the small proportion of passengers in the detection image,the ECA attention module is introduced in the feature fusion stage to weaken the background infor-mation.Finally,the WIoU loss function is adopted to replace the original CIoU function to im-prove the convergence ability of the model.Through experimental analysis,compared with the original YOLOv8 algorithm,the mAP@.5 of the algorithm in this paper is increased by 2.2％,and the number of parameters is reduced by 13.3％.
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