Optimal Camera Placement for Providing Angular Coverage in Wireless Video Sensor Networks
Optimal Camera Placement for Providing Angular Coverage in Wireless Video Sensor Networks
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DOI：
10.1109/tc.2013.45
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发表时间：
2014-07
影响因子：
3.7
通讯作者：
Enes Yildiz;Kemal Akkaya;Esra Sisikoglu;M. Sir
中科院分区：
文献类型：
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作者：
Enes Yildiz;Kemal Akkaya;Esra Sisikoglu;M. Sir
无线视频传感器网络（WVSNs）提供了机会，使用大量的低成本低分辨率的无线摄像机传感器的大规模户外远程监控任务。相机传感器部署对于实现良好的覆盖范围、准确性和容错性至关重要。特别地，随着无线摄像机的成本降低，冗余摄像机部署是有吸引力的，以便获得事件的多个不同视图以用于改进的事件识别。如果事件的捕获跨越360°，则这被称为角度覆盖。在本文中，我们考虑的问题，确定最佳的摄像机放置，以实现角覆盖连续在一个给定的区域。我们开发了一个双层算法来找到最小成本的摄像机放置。在第一级中，我们运行一个主问题，该主问题识别相机放置点，以实现从感兴趣区域中选择的离散点集的角度覆盖。接下来，我们使用一个子问题来识别连续区域中未被前一次运行的主问题中放置的摄像机覆盖的点。然后，我们将这些未覆盖的点添加到主问题的离散点集，并重新运行主问题。我们继续迭代地运行主问题和子问题，直到子问题变得不可行，表明整个区域都被覆盖。在数值实验中，我们考虑了两种情况：1）放置具有固定分辨率的同质相机; 2）放置具有不同特性和分辨率的异质相机。我们还为该区域的不同部分引入了不同的分辨率要求，并放置相机以满足所需的分辨率。数值结果表明，相对于现有的方法的双层方法的优越性。
Wireless Video Sensor Networks (WVSNs) provide opportunities to use large number of low-cost low-resolution wireless camera sensors for large-scale outdoor remote surveillance missions. Camera sensor deployment is crucial in achieving good coverage, accuracy and fault tolerance. In particular, with the decreased costs of wireless cameras, redundant camera deployment is attractive in order to get multiple disparate views of events for improved event identification. If the capturing of an event spans 360°, this is referred to as angular coverage. In this paper, we consider the problem of determining optimal camera placement to achieve angular coverage continuously over a given region. We develop a bi-level algorithm to find the minimum-cost camera placement. In the first level, we run a master problem that identifies the camera placement points to achieve angular coverage of a discrete set of points selected from the region of interest. Next, we use a sub-problem to identify points in the continuous region that are not covered by the cameras placed in the previous run of the master problem. We then add these uncovered points to discrete point set of the master problem and re-run the master problem. We continue running the master and sub-problems iteratively until the sub-problem becomes infeasible indicating that the entire region is covered. In the numerical experiments, we consider two cases 1) placement of homogeneous cameras with fixed resolutions; and 2) placement of heterogeneous cameras with different characteristics and resolutions. We also introduce varying resolution requirements for different parts of the region and place the cameras such that the required resolution is satisfied. The numerical results show the superiority of the bi-level approach respect to existing approaches.