期刊文献+

基于场边界线的多摄像机智能监控系统研究 被引量:3

Research on multi-camera intelligent monitoring system based on field of view lines
在线阅读 下载PDF
导出
摘要 伴随视频监控系统的普及,多摄像机智能视频监控技术得到了广泛的研究和应用。特别是视频监控中的运动目标检测分割、运动目标跟踪和多摄像机协同技术,成为计算机视觉领域研究的热点。单摄像机跟踪常被应用的监控范围限制,当监控场景是一个室外环境或需要一个较大的观测范围时,常需要多摄像机进行多物体跟踪。为了建立一套有效的多摄像机智能监控系统,提出一种基于摄像机视野的重叠区域的协同监控方法,找出重叠区域的边界线即场边界线,旨在解决单摄像机监控范围有限的问题,实现对某一场景进行全景监控。在多摄像机系统中各个摄像机的场边界线在其他摄像机中可见的情况下,给出寻找它们的方法。基于此,可基本确定在多摄像机中的运动目标对应关系,获取多摄像机的拓扑关系。 With the popularization of video monitoring system,the multi-camera intelligent video monitoring technology has been widely studied and applied. The moving object detection and segmentation,moving target tracking,and multi-camera cooperation technology have become the research focus in computer vision field. Single camera tracking is limited by the monitoring scope. When the monitoring scene is an outdoor environment or needing a larger monitoring scope,multi-camera are required to track multi-object. A coordination monitoring method of overlapping region based on camera visual field is proposed to establish an effective multi-camera intelligent monitoring system. The field of view(FOV)lines are found out in the overlapping region to solve the limited monitoring scope of the single camera. The panorama monitoring for a certain scene is realized. The way how to find the FOV lines in multi-camera system is provided when each camera's FOV lines can be seen by other cameras. The corresponding relationships of moving object in multi-camera can be ensured basically,and the topological relation of multi-camera can be acquired.
作者 张益男 袁杰
出处 《现代电子技术》 北大核心 2015年第21期6-10,共5页 Modern Electronics Technique
基金 江苏省自然科学基金(BK20131280) 南京大学金陵学院教学改革资金项目(0010111208)
关键词 运动目标检测 多摄像机协同 场边界线 全景监控 moving object detection multi-camera cooperation field of view line panorama monitoring
  • 相关文献

参考文献10

二级参考文献88

  • 1韩晓波.基于背景建模和动态分块的目标跟踪[J].电子技术(上海),2010(10):21-23. 被引量:2
  • 2孙中森,孙俊喜,宋建中,乔双.一种抗遮挡的运动目标跟踪算法[J].光学精密工程,2007,15(2):267-271. 被引量:30
  • 3王长军,朱善安.基于Mean Shift的目标平移与旋转跟踪[J].中国图象图形学报,2007,12(8):1367-1371. 被引量:10
  • 4Weiser M. The computer for the twenty -first century [J]. Scientific American, 1991, 265(3) : 94 - 104.
  • 5Kim W, Hong S, Lee J. An active contour model using image flow for tracking a moving object [C]// Proc IEEE/RSJ International Conference on Intelligent Robots and Systems. Kyongju, Korea: IEEE Press, 1999: 216-221.
  • 6Kass M, Witkin A, Terzopoulous D. Snakes: Active contour models [C]// Proc IEEE International Conference on Computer Vision. London, UK: IEEE Press, 1987: 259- 268.
  • 7Isard M, Blake A. Condensation.. Conditional density propagation for visual tracking [J]. International Journal of Computer Vision, 1998, 28(1): 5-28.
  • 8Carpenter J, Clifford P, Fearnhead P. Improved particle filter for nonlinear problems[J].IEEE Proceedings: Radar, Sonar and Navigation, 1999, 146(1) : 2 - 7.
  • 9Forsyth D A, Ponce J. Computer Vision: A Modern Approach [M]. New York, USA:Prentice Hall, 2002.
  • 10Tenenbaum J B, deSilva V, Langford J C. A global geometric framework for nonlinear dimensionality reduction [J]. Science, 2000, 290(5500): 2319-2323.

共引文献151

同被引文献37

引证文献3

二级引证文献24

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部