Coordinating Multiple Cameras to Assist Tracking Moving Objects Based on Network Topological Structure

被引:0
|
作者
Zheng Y. [1 ]
Xu T. [1 ]
Xu D. [1 ]
Yang T. [1 ]
Li X. [1 ]
机构
[1] Ministry of Education Key Laboratory of Geographical Information Science, East China Normal University, Shanghai
来源
Li, Xiang (xli@geo.ecnu.edu.cn) | 1600年 / Editorial Board of Medical Journal of Wuhan University卷 / 42期
关键词
Multi-camera coordination; Multi-camera search; Network topological structure; Trackingmoving objects;
D O I
10.13203/j.whugis20150155
中图分类号
学科分类号
摘要
Due to the factors of large amount of monitors and data, event changes quickly and so on, security surveillance system can't track moving objects timely and effectively in response to emergencies.The paper presents a coordinating multiple cameras approach to assist tracking moving objects based on network topological structure in urban environment. Firstly, the fields of view of cameras were abstracted as points located in node-arc model with linear referencing system to construct a network topological structure between cameras and urban road. According to the network topological structure, we search some cameras which have spatial neighborhood relation with first camera, and analyzing proximity relation of cameras and to find out the time difference between cameras. Then we set some cameras as the main monitoring group for tracking moving objects. As the time goes on, we could update the monitoring group by replacing some cameras in which moving objects can't appear according to the queue principle. In order to verify the validity of the cooperative multi-camera approach, we establish a system based on traffic simulation model that simulates the real traffic circumstance, and randomly select some moving objects that generated by the model to have a test. The experiment result demonstrates that the method is able to provide directive information consisted of map and surveillance information which can assist monitors to track moving targets successfully and effectively. © 2017, Research and Development Office of Wuhan University. All right reserved.
引用
收藏
页码:1117 / 1122
页数:5
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