铁道运输与经济2024，Vol.46Issue(1)：109-115,7.DOI:10.16668/j.cnki.issn.1003-1421.2024.01.15
基于违禁品检测和人脸表情识别的铁路客运站安检风险评估技术研究
Risk Assessment Mechanism of Security Inspection in Railway Passenger Station Based on Prohibited Substance Detection and Facial Expression Recognition
摘要
Abstract
With the rapid development of high speed rail and the flow of people in railway stations increasing,the probability of risk events in the railway system is also increasing.It is no longer sufficient to rely on security personnel to identify risks.To better assess station safety risks and reduce the dependence of station safety assessment on manpower,this paper proposed a risk assessment mechanism for station personnel and items based on deep learning.First,the trained YOLOv5s model was adopted to detect dangerous goods in security X-ray photos.Secondly,the trained ResNet50 model was applied to recognize the facial expressions at the exit of the station security inspection machine.Finally,the paper established a risk assessment mechanism for station personnel and items that combined dangerous goods detection and facial expression recognition.The simulation results show that the adopted method can more accurately detect and recognize dangerous objects and facial expressions.The proposed risk assessment mechanism reduces the reliance on manpower in the security inspection.It can comprehensively help station staff prevent security inspection risks and provide a guarantee for the safety of the station.关键词
智能交通/风险评估/目标检测/违禁品/铁路运输/表情识别Key words
Intelligent Transportation/Risk Assessment/Target Detection/Dangerous Goods/Railway Transportation/Facial Expression Recognition分类
交通工程引用本文复制引用
彭凯贝,吕晓军,李超,魏昊..基于违禁品检测和人脸表情识别的铁路客运站安检风险评估技术研究[J].铁道运输与经济,2024,46(1):109-115,7.基金项目
国家自然科学基金项目(61972016) （61972016）
北京经纬信息技术有限公司科研项目(DZYF23-30) （DZYF23-30）
