摘要
针对铁路视频监控系统人工监控容易产生疏漏的问题,研究计算机智能铁路入侵检测系统,不失一般性地提出了一种针对n维入侵目标及m维基本运动过程所组成的多目标融合铁路入侵行为模型。经实时监控视频实验验证,该模型具有普遍适用性,以该模型为核心的智能识别算法对入侵行为的识别成功率可达70%。该模型对铁路入侵物体运动定位、跟踪以及入侵行为的分析具有重要意义。
Aiming at the problem that manualmonitoring of railway video monitoring system is liable to produce omissions, this paper studies the computer intelligent railway intrusion detection system, and generally puts forward a multi objective fusion railway intrusion behavior model which is composed for n dimensional intrusion target and m dimensional basic movement process. The experimental results of real time monitoring video show that the model has universal applicability, and the success rate of the intelli gent recognition algorithm based on the model can reach 70%. The model is of great significance to the lo cation, tracking and intrusion behavior analysis of railway intruding objects.
作者
朱亚男
李冰毅
房楠
Zhu Yanan;Li Bingyi;Fang Nan(Department of Traction Power,Xi＇an Railwaj Vocational ＆ Technical Institute,Xi＇an 710014,China)
出处
《甘肃科学学报》
2018年第6期103-106,139,共5页
Journal of Gansu Sciences
基金
西安铁路职业技术学院研究项目课题"基于智能视频技术的铁路入侵检测算法研究"(XTZY18G03)
关键词
智能监控
多目标融合
入侵行为
铁路安全
Intelligent monitoring
Multi target fusion
Intrusion behavior
Railway safety
