Implementation of Real-Time Vehicle Tracking in City-Scale Video Network

被引:2
作者
Pu, Fangling [1 ]
Xie, Wentao [1 ]
Cheng, Yao [1 ]
Xu, Xin [1 ]
机构
[1] Wuhan Univ, Sch Elect Informat, Collaborat Innovat Ctr Geospatial Technol, Wuhan, Peoples R China
关键词
Gaussian mixture model; geospatial and temporal connection model; video surveillance network; vehicle tracking; CAMERA; MODELS;
D O I
10.1080/01969722.2016.1158548
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Tracking unexpected warning vehicles is required for quick response to security incident. To realize real-time vehicle tracking in a large-scale video surveillance network, a geospatial and temporal connection (GSTC) model is introduced to model the connection between videos. The transition time between videos is modeled by a Gaussian mixture model (GMM). With the developed plug-ins based on GSTC and GMM, the video streams of defined geospatial neighbors are automatically called in with the video stream that the object appears in during the tracking process. Experiments show that the ratio of success of real-time tracking is largely increased.
引用
收藏
页码:249 / 260
页数:12
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