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Avoiding Overlap Grade for Improving Performance of Target Region in Wireless Sensor Networks

机译:避免重叠等级以提高无线传感器网络中目标区域的性能

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Target finding without predicted information of the target is one of the critical areas of development, the major area here propose a new sensor selection solution that improves the accuracy of target localization without prior knowledge of the target in wireless visual sensor networks. The proposed solution exploits the properties of the overlap region of the target in images: the more overlap grade, the more cameras project images of the target in the same direction; the greater overlap area, the higher possibility that the target is located in the region. The authors formulate the sensor selection problem as one of maximising the utility of multiplying the overlap grade by the overlap area gained from a set of sensors. Simulation results show the effectiveness of this approach of sensor selection in terms of improving the accuracy of target localization.
机译:没有目标的预测信息的目标发现是发展的关键领域之一,这里的主要领域提出了一种新的传感器选择解决方案,该解决方案可以提高目标定位的准确性,而无需事先了解无线视觉传感器网络中的目标。所提出的解决方案利用了目标在图像中的重叠区域的特性:重叠度越高,相机在同一方向上投影目标图像的数量就越多;重叠区域越大,目标位于该区域的可能性越高。作者将传感器选择问题表述为最大程度地利用重叠等级乘以从一组传感器获得的重叠面积的效用。仿真结果表明,这种传感器选择方法在提高目标定位精度方面是有效的。

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