调整天文源探测软件，以帮助探测无人驾驶航空系统获得的热图像中的动物
Adapting astronomical source detection software to help detect animals in thermal images obtained by unmanned aerial systems
摘要：
在本文中，我们描述了一个无人驾驶航空系统配备了热红外相机和软件管道，我们已经开发出监测动物种群的保护目的。我们采用多学科方法来解决这一问题，使用免费提供的天文源检测软件和天文学家的相关专业知识，有效可靠地检测航空热红外镜头中的人类和动物。将这个天文探测软件与现有的机器学习算法结合到一个单一的、自动化的、端到端的管道中，我们使用在一个受控的、类似野外的环境中拍摄的空中视频片段来测试该软件。我们证明了管道的可靠性，并描述了它如何用于估计不同观测数据集对给定类型对象的完整性，作为高度，观测条件等的函数-这是将视频片段转换为科学有用信息的关键一步，例如不同动物物种的空间分布和密度。最后，已经证明了该系统的潜在效用，我们描述了我们正在采取的步骤，以适应该系统的工作在外地，特别是在世界各地的国家公园濒危物种的系统监测。
英文摘要：
In this paper we describe an unmanned aerial system equipped with a thermal-infrared camera and software pipeline that we have developed to monitor animal populations for conservation purposes. Taking a multi-disciplinary approach to tackle this problem, we use freely available astronomical source detection software and the associated expertise of astronomers, to efficiently and reliably detect humans and animals in aerial thermal-infrared footage. Combining this astronomical detection software with existing machine learning algorithms into a single, automated, end-to-end pipeline, we test the software using aerial video footage taken in a controlled, field-like environment. We demonstrate that the pipeline works reliably and describe how it can be used to estimate the completeness of different observational datasets to objects of a given type as a function of height, observing conditions etc. -- a crucial step in converting video footage to scientifically useful information such as the spatial distribution and density of different animal species. Finally, having demonstrated the potential utility of the system, we describe the steps we are taking to adapt the system for work in the field, in particular systematic monitoring of endangered species at National Parks around the world.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
