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The Video Collaborative Localization of a Miner’s Lamp Based on Wireless Multimedia Sensor Networks for Underground Coal Mines

机译:基于无线多媒体传感器网络的煤矿井下矿灯的视频协作定位

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Based on wireless multimedia sensor networks (WMSNs) deployed in an underground coal mine, a miner’s lamp video collaborative localization algorithm was proposed to locate miners in the scene of insufficient illumination and bifurcated structures of underground tunnels. In bifurcation area, several camera nodes are deployed along the longitudinal direction of tunnels, forming a collaborative cluster in wireless way to monitor and locate miners in underground tunnels. Cap-lamps are regarded as the feature of miners in the scene of insufficient illumination of underground tunnels, which means that miners can be identified by detecting their cap-lamps. A miner’s lamp will project mapping points on the imaging plane of collaborative cameras and the coordinates of mapping points are calculated by collaborative cameras. Then, multiple straight lines between the positions of collaborative cameras and their corresponding mapping points are established. To find the three-dimension (3D) coordinate location of the miner’s lamp a least square method is proposed to get the optimal intersection of the multiple straight lines. Tests were carried out both in a corridor and a realistic scenario of underground tunnel, which show that the proposed miner’s lamp video collaborative localization algorithm has good effectiveness, robustness and localization accuracy in real world conditions of underground tunnels.
机译:基于部署在地下煤矿中的无线多媒体传感器网络(WMSN),提出了矿工的灯视频协作定位算法,以将矿工定位在光照不足和地下隧道分叉结构的场景中。在分叉区域,沿隧道的纵向方向部署了多个摄像头节点,以无线方式形成协作集群,以监视和定位地下隧道中的矿工。在地下隧道照明不足的情况下,帽灯被视为矿工的特征,这意味着可以通过检测其帽灯来识别矿工。矿灯将映射点投射在协作摄像机的成像平面上,并且映射点的坐标由协作摄像机计算。然后,在协作摄像机的位置及其对应的映射点之间建立多条直线。为了找到矿灯的三维(3D)坐标位置,提出了一种最小二乘法来获得多条直线的最佳交点。在走廊和地下隧道的真实场景中都进行了测试,结果表明,所提出的矿灯视频协同定位算法在地下隧道的实际环境中具有良好的有效性,鲁棒性和定位精度。

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