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Measuring height of high-voltage transmission poles using unmanned aerial vehicle (UAV) imagery

机译:使用无人机(UAV)图像测量高压输电杆的高度

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Aerial imagery is important in remote sensing applications. Unmanned aerial vehicle (UAV) has a wide range of applications in remote sensing and presents a substantial cost-effective solution when monitoring objects on the earth's surface. Moreover, object detection and classification are important aspects of global information system, especially for remote sensing applications and power line monitoring, which are essential for the proper distribution of electricity to consumers. Manual inspection consumes much time and involves risk, especially in remote areas that host dangerous wildlife; hence, UAV-based approaches are more feasible for such monitoring. The authors propose an UAV approach that utilises a digital surface model and incorporates a stereo matching algorithm based on UAV stereo images. The proposed algorithm was based on a graph-cut (GC) algorithm that measured the disparity map. Results were compared with well-known algorithms; including, for example, global and local stereo matching algorithms. The proposed solution introduces and integrates ordering constraints along with a submodular energy minimisation function to/with the GC algorithm to enhance performance. The authors measured sensitivity and recall for all parameters against ground truth data for differently cropped images of 16 power poles. Results showed that the proposed model performed more accurately compared to extant methods.
机译:航空影像在遥感应用中很重要。无人机(UAV)在遥感中具有广泛的应用范围,当监视地球表面的物体时,它是一种具有成本效益的解决方案。此外,对象检测和分类是全球信息系统的重要方面,尤其是对于遥感应用程序和电力线监控而言,这对于向消费者正确分配电力至关重要。手动检查会耗费大量时间并带来风险,尤其是在收容危险野生生物的偏远地区;因此,基于无人机的方法对于这种监视更为可行。作者提出了一种利用数字表面模型并结合基于无人机立体图像的立体匹配算法的无人机方法。所提出的算法基于测量视差图的图割(GC)算法。将结果与众所周知的算法进行比较;包括,例如,全局和局部立体声匹配算法。所提出的解决方案将排序约束以及子模块能量最小化功能引入并集成到GC算法中,或与GC算法集成,以提高性能。作者针对16个电线杆的不同裁剪图像,针对地面真实数据测量了所有参数的灵敏度和召回率。结果表明,与现有方法相比,所提出的模型执行起来更准确。

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