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P2P-based Geometric Computation Method for Extracting ROI from Ubiquitous Video Cameras

机译:基于P2P的几何计算方法,用于从无处不在的视频摄像机中提取ROI

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This paper proposes a method for extracting the ROI using geometric computations, to obtain information of commonly-interested objects by multiple users. The authors use P2P Delaunay Network to share the regional information shot by cameras with peers, and extract the most intersecting area of camera ranges as ROI. In P2P Delaunay Network, nodes and edges refer to as computers and their connections. This proposed method can construct P2P Delaunay Network using locations of mobile devices as GPS phones or PDAs equipped with a camera, and process computations distributively with these devices. Thereby, a P2P Delaunay network can be constituted, without using the computer resource of other settlements. The method first partitions the plane and assigns the partitions to nodes according to their locations using P2P Delaunay Network. Then, each camera propagates its camera range information to nodes, and each node thus processes computation distributively. The node which has received multiple camera range information computes the intersecting area within its Voronoi region. Finally, the ROI can be determined, by computing the most intersecting area among all nodes. The authors examine the proposed method by evaluating the frequency of region partitioning and data transfer for each node through numerical simulation.
机译:本文提出了一种利用几何计算提取ROI的方法,以便由多个用户获取共同感兴趣的对象的信息。作者使用P2P Delaunay网络与摄像机拍摄的区域信息与同行分享,并提取相机范围的最多交叉区域作为ROI。在P2P Delaunay网络中,节点和边缘称为计算机及其连接。该所提出的方法可以使用移动设备的位置作为配备有相机的GPS电话或PDA来构建P2P Delaunay网络,以及通过这些设备的分布地处理计算。因此,可以构成P2P DelaUnay网络,而不使用其他定居点的计算机资源。该方法首先使用P2P Delaunay网络根据其位置分区平面并将分区分配给节点。然后,每个摄像机将其相机范围信息传播给节点,并且每个节点因此处理分布性地处理计算。已经接收到多个相机范围信息的节点计算其Voronoi区域内的交叉区域。最后,可以通过计算所有节点中的最相交的区域来确定ROI。作者通过数值模拟评估每个节点的区域划分和数据传输的频率来检查所提出的方法。

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