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Compute-Efficient Geo-Localization of Targets from UAV Videos: Real-Time Processing in Unknown Territory

机译:无人机视频中目标的高效计算地理定位:未知地区的实时处理

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Unmanned Air Vehicles (UAVs) have crucial roles to play in traditional warfare, asymmetric conflicts, and also civilian applications such as search and rescue operations. Though satellites provide extensive coverage and capabilities crucial to many remote sensing tasks, UAVs have distinct edge over satellites in dynamic situations due to shorter revisit times and desired area/time coverage. The course, speed and altitude of a UA V can be dynamically altered, details of an activity of interest monitored by loitering over the area as desired. A fundamental requirement in most UAV operations is to find geo-coordinates of an object in the captured image. Most small, low-cost UAVs use low-cost, less accurate sensors. Matching with pre-registered images may not be possible in areas with low details or in emergency situations where terrain may have undergone severe sudden changes. In these situations that demand near real-time results and wider coverage, it is often enough to provide approximate results as long as bounds on accuracies can be established. Even when image registration is possible, it can benefit from these bounds to reduce search space thereby saving execution time. The prime contributions of this paper are computation of location of target anywhere in the image even at larger slant ranges, optimized algorithm to compute terrain elevation at target point, and use of visual simulation tool to validate the model. Analysis from simulation and results from real UA Vflights are presented.
机译:无人飞行器(UAV)在传统战争,非对称冲突以及民用应用(例如搜救行动)中起着至关重要的作用。尽管卫星提供了对许多遥感任务至关重要的广泛的覆盖范围和功能,但由于动态访问时间较短且所需的区域/时间覆盖范围较大,因此在动态情况下无人机具有优于卫星的优势。 UA V的航向,速度和高度可以动态更改,可以通过在所需区域中游荡来监视感兴趣活动的细节。大多数无人机操作的基本要求是在捕获的图像中找到对象的地理坐标。大多数小型低成本无人机都使用低成本,精度较低的传感器。在低细节区域或在紧急情况下地形可能发生了严重的突然变化,可能无法与预先注册的图像匹配。在这些情况下,需要接近实时的结果和更广泛的覆盖范围,只要可以确定精度范围,通常足以提供近似结果。即使可以进行图像配准,也可以从这些范围中受益,以减少搜索空间,从而节省执行时间。本文的主要贡献是即使在较大的倾斜范围内,也可以计算目标在图像中任何位置的位置,优化算法以计算目标点处的地形高程以及使用可视化仿真工具来验证模型。给出了仿真分析和实际UA Vflights的结果。

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