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智能网络视频监控系统 被引量:5

Intelligence Network Video Surveillance System
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摘要 设计一种智能网络视频监控系统,实现实时监控和目标实时跟踪功能。系统前端使用网络摄像机采集实时图像,通过网络服务器将实时图像传输给网络用户终端,在终端实现实时监控操作。以颜色信息作目标特征,采用均值偏移算法实现对目标人物的实时跟踪。实验表明,该系统具有良好的稳定性与实时性。 An intelligence network video surveillance system for both real-time surveillance and real-time object tracking is designed. The video image is captured by the network cameras in system front-end, and sent to the network user terminals through the network server. At the port of user terminal, the real-time surveillance operations can be operated. Use color information as the target feature, mean shift is used for real-time object tracking. Experiment results show that the system is stable in real-time.
出处 《兵工自动化》 2009年第12期71-74,共4页 Ordnance Industry Automation
关键词 智能网络视频监控 均值偏移 PI算法 Intelligence network video surveillance Mean shift PI algorithm
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参考文献5

  • 1Comaniciu D, Ramesh V., Meer P. Real-Time tracking of non-rigid objects using mean shift [C]//IEEE International Proceeding on Computer Vision and Pattern Recognition, Stoughton: Printing House, 2000(2): 142-149.
  • 2Comaniciu D, Ramesh V. prediction for efficient object J, eds. Proc. of the IEEE Int'l (ICIP). 2000: 70-73. Mean shift and optimal tracking. Mojsilovic A,Hu Conf. on Image Processing.
  • 3Collins RT. Mean shift blob tracking through scale space. Proc. Of the Conf. on Computer Vision and Pattern Recognition (CVPR). 2003: 18-20.
  • 4Cheng YZ. Mean shift, mode seeking, and clustering. IEEE Trans. on Pattern Analysis and Machine Intelligence, 1995, 17(8): 790-799.
  • 5Comaniciu D, Ramesh V, P. MEER. Kernel-based object tracking [J]. IEEE Transactions. on Pattern Analysis and Machine Intelligence, 2003, 25(5): 564-577.

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