首页 | 本学科首页   官方微博 | 高级检索  
     检索      

实时异常轨迹检测方法及其应用
引用本文:夏英,刘申艺.实时异常轨迹检测方法及其应用[J].重庆邮电大学学报(自然科学版),2011,23(4):496-499.
作者姓名:夏英  刘申艺
作者单位:1. 西南交通大学信息科学与技术学院,四川成都610031;重庆邮电大学计算机学院,重庆400065
2. 重庆邮电大学计算机学院,重庆,400065
基金项目:重庆市计算机网络与通信技术重点实验室开放基金(CY-CNCL-2009-01);重庆市科委科技项目(CSTC2009CB2015)
摘    要:利用内置GPS的移动终端可以获取移动对象的运动轨迹,可用于分析移动对象的运动行为.在公共交通、医疗监护、物流运输等应用领域,移动对象的运动轨迹受路网约束且大多需要预先设定.考虑到偏离预先设定的正常轨迹可能预示着某种异常,及时准确地进行异常轨迹检测是非常必要的.从时间序列分析的角度,提出一种实时异常轨迹检测算法,在预先设...

关 键 词:移动对象  轨迹  异常检测  Hausdorff距离
收稿时间:2010/11/30 0:00:00

Real time trajectory anomaly detection method and its application
XIA Ying,LIU Shen-yi.Real time trajectory anomaly detection method and its application[J].Journal of Chongqing University of Posts and Telecommunications,2011,23(4):496-499.
Authors:XIA Ying  LIU Shen-yi
Institution:School of Information Science and Technology, Southwest Jiaotong University, Chengdu 600031, P.R.China
Abstract:Trajectory of moving object can be acquired by using GPS-embedded mobile terminal which can be used for analysing moving patterns. In many fields such as public transportation, medical treatment and logistics service, the trajectories of moving objects are constrained by road network and mostly pre-defined. Considering that deviating from the normal trajectory might imply some problems, it is necessary to detect it in real time. From the view of temporal sequence analysis, this paper proposes a real time trajectory anomaly detection algorithm. During the valid detection period, partial sequence of the real trajectory is dynamic selected and the scope of normal trajectory is adjusted correspondingly, and the improved modified Hausdorff distance is used to reflect the degree of deviation. Experiments show that the proposed algorithm compared with the conventional map matching method is more efficient in accuracy and realtime.
Keywords:moving object  trajectory  anomaly detection  Hausdorff distance
本文献已被 万方数据 等数据库收录!
点击此处可从《重庆邮电大学学报(自然科学版)》浏览原始摘要信息
点击此处可从《重庆邮电大学学报(自然科学版)》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号