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A new method to combine detection and tracking algorithms for fast and accurate human localization in UAV-based SAR operations

机译:结合检测和跟踪算法的新方法,可在基于无人机的SAR操作中实现快速准确的人体定位

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This paper presents the study and the evaluation of GPS/GNSS techniques combined with advanced image processing algorithms for the precise detection, positioning and tracking of distressed humans. In particular, the issue of human detection on both terrestrial and marine environments, as the human silhouette in a marine environment may differ substantially from a land one, is addressed. A robust approach, including an adaptive distressed human detection algorithm running every N input image frames combined with a much faster human tracking algorithm, is proposed. Real time or near-real-time distressed human detection rates, under several illumination and background conditions, can be achieved using a single, low cost dayight NIR camera. It is mounted onboard a fully autonomous UAV for Search and Rescue (SAR) missions. Moreover, the collection of a novel dataset, suitable for training the computer vision algorithms is also presented. Details about both hardware and software configuration as well as the assessment of the proposed approach performance are discussed. Last, a comparison of the proposed approach to other human detection methods used in the literature is presented.
机译:本文介绍了结合先进的图像处理算法进行GPS / GNSS技术的研究和评估,以精确检测,定位和跟踪遇险人员。特别地,解决了在陆地和海洋环境两者上的人类检测的问题,因为海洋环境中的人类轮廓可能与陆上的轮廓大不相同。提出了一种鲁棒的方法,其中包括每N个输入图像帧运行一次的自适应窘迫人体检测算法,并结合了一种更快的人体跟踪算法。使用单个低成本的日/夜NIR摄像机,可以在几种照明和背景条件下实现实时或接近实时的人体不适检测率。它安装在用于搜索和救援(SAR)任务的完全自主的无人机上。此外,还介绍了适用于训练计算机视觉算法的新型数据集。讨论了有关硬件和软件配置以及对拟议方法性能的评估的详细信息。最后,将所提出的方法与文献中使用的其他人体检测方法进行了比较。

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