基于视频序列推理的高铁周界入侵在线检测方法  

Online detection method for high-speed railway perimeter intrusion based on video sequence inference

作　　者：汪洋 王森森 王瑞 胡昊 刘跃虎[2] WANG Yang;WANG Sensen;WANG Rui;HU Hao;LIU Yuehu(School of Software Engineering,Xi’an Jiaotong University,Xi’an 710049,China;College of Artificial Intelligence,Xi’an Jiaotong University,Xi’an 710049,China;Institute of Computing Technologies,China Academy of Railway Sciences Corporation Limited,Beijing 100081,China)

机构地区：[1]西安交通大学软件学院,西安710049 [2]西安交通大学人工智能学院,西安710049 [3]中国铁道科学研究院集团有限公司电子计算技术研究所,北京100081

出　　处：《铁路计算机应用》2024年第9期1-5,共5页Railway Computer Application

摘　　要：针对高速铁路(简称:高铁)周界入侵事件检测任务中面临的事件时序依赖性导致的建模难度高、样本类间差异小的问题,提出一种基于视频序列推理的高铁周界入侵在线检测方法。利用门控循环单元捕捉视频序列的动态特征,区分不同事件差异;通过Transformer编码器构建视频序列的全局时序依赖关系,理解事件的全局上下文;使用Transformer解码器的预测结果作为补充信息,辅助当前事件的检测。实验结果显示,与传统检测方法相比,该方法能够更准确地进行高铁周界入侵事件检测,具有推广价值。This paper proposed an online detection method for high-speed railway perimeter intrusion based on video sequence inference to address the issues of high modeling difficulty and small differences between sample classes caused by event temporal dependency in the detection of high-speed railway perimeter intrusion events.The paper utilized gated loop units to capture the dynamic features of video sequences,distinguished differences between different events,constructed global temporal dependencies of video sequences through Transformer encoders,understood the global context of events,and used the prediction results of Transformer decoders as supplementary information to assist in the detection of current events.The experimental results show that compared with traditional detection methods,this method can more accurately detect high-speed rail perimeter intrusion events and has promotional value.

关 键 词：周界入侵 监控视频 门控循环单元 自注意力机制 时序依赖 

分 类 号：U298[交通运输工程—交通运输规划与管理]