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Generation of an Optimum Patrol Course for Mobile Surveillance Camera

机译:生成用于移动监控摄像头的最佳巡逻课程

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摘要

Video surveillance systems are becoming increasingly important for crime investigation and deterrence, and the number of cameras installed in public space is increasing. However, many cameras installed at fixed positions are required to observe a wide and complex area. In order to efficiently observe such a wide area at lower cost, mobile robots are an attractive option. In this paper, we propose a method for determining the traveling route of a mobile surveillance camera. Our method is based on mixed integer linear programming and obtains an optimum traveling route such that a camera with a certain visual angle and visual distance can observe the entire region at the shortest intervals. Through our experiments, we apply this method to several artificially generated data and data for a real university campus and demonstrate that effective patrol courses for specified mobile surveillance cameras can be generated.
机译:视频监视系统对于犯罪调查和威慑变得越来越重要,并且在公共场所安装的摄像头数量也在增加。但是,需要将许多安装在固定位置的摄像机观察宽阔而复杂的区域。为了以较低的成本有效地观察如此大的区域,移动机器人是一种有吸引力的选择。在本文中,我们提出了一种确定移动监控摄像机行进路线的方法。我们的方法基于混合整数线性规划,并获得了最佳的行驶路线,从而使具有一定视角和距离的相机可以以最短的间隔观察整个区域。通过我们的实验,我们将此方法应用于了一些人工生成的数据以及一个真正的大学校园的数据,并证明可以为指定的移动监控摄像机生成有效的巡逻课程。

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