一种针对轨交大客流环境的新型目标检测算法研究

Research on a New Target Detection Algorithm for the Large Passenger Flow Environment of Metro

轨道交通行业具有人口密度大、人流集中、场所特殊的特点,一直以来都是社会公共安全危险与风险的重点关注领域。近年来,人工智能、计算机视觉以及大数据技术迅猛发展为轨道交通安全运营带来了新的机遇和挑战。文章旨在深入研究轨道交通行业特定的大客流环境下目标检测算法的模型,并提出一个新型目标检测算法技术框架,力争解决智能视频分析技术在轨道交通行业落地难的难题,为后续在北京地铁全路网范围内工程化落地提供技术准备和参考。

The rail transit industry has the characteristics of high population density,concentrated flow of people and special places.This has always been a key area of concern for social and public safety hazards and risks.In recent years,the rapid development of artificial intelligence,computer vision and big data technologies has brought new opportunities and challenges to the safe operation of rail transit.This paper aims to deeply study the model of the target detection algorithm in the specific large passenger flow environment of the rail transit industry and propose a technical framework for a new target detection algorithm,striving to solve the difficult problem of intelligent video analysis technology in the rail transit industry.Provide technical preparation and reference for the engineering implementation of the entire subway network.