The auroral arc is the typical track of the interaction between the solar wind and the Earth's magnetosphere. A sketch of skeletons for arc-like aurora is usually used to describe auroral structures, such as vortex, fold and curl structures, etc. With artificial intelligence technologies, sketching auroral skeleton structure (AuroSS) in all-sky images enables automatic detection and measurement of aurora arcs in very large amounts of ground-based auroral observation data. The skeleton is a highly characterizing topological structure that has been extensively studied in the field of computer vision. However, AuroSS is not the medial axis of auroral shapes and a large number of accurate AuroSS annotations are not available. It is difficult to detect AuroSS by using an unsupervised or fully-supervised method. In this paper, we formulate the automatic AuroSS extraction to learn a mapping from an all-sky auroral image to a ridge style AuroSS. Without accurate AuroSS annotations, emission ridge and coarse localization of aurora are incorporated to generate pseudo-labels of AuroSS. A series of functional weakly supervised models are trained and cascaded to achieve AuroSS detection. Experimental results on auroral images obtained from all-sky imagers at Yellow River Station (YRS) show that the detected AuroSS is consistent with that of human visual perception. Based on the obtained AuroSS, the orientations and lengths of auroral arcs can be estimated automatically. By browsing the temporal variation in arc orientation from dusk to dawn, we can acquire synoptic observations of auroral activities at YRS.

中文翻译：

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在全天图像中自动绘制极光骨架结构以测量极光弧

极光弧是太阳风与地球磁层相互作用的典型轨迹。弧形极光骨架草图通常用于描述极光结构，如涡旋、折叠和卷曲结构等。借助人工智能技术，在全天图像中草绘极光骨架结构（AuroSS）可以实现自动检测和测量大量地面极光观测数据中的极光弧。骨架是一种高度表征的拓扑结构，在计算机视觉领域得到了广泛的研究。然而，AuroSS 不是极光形状的中轴，并且没有大量准确的 AuroSS 注释。使用无监督或完全监督的方法很难检测 AuroSS。在本文中，我们制定了自动 AuroSS 提取，以学习从全天空极光图像到山脊样式 AuroSS 的映射。如果没有准确的 AuroSS 注释，则会合并发射脊和极光的粗定位来生成 AuroSS 的伪标签。一系列功能性弱监督模型经过训练和级联以实现 AuroSS 检测。黄河站全天空成像仪获得的极光图像的实验结果表明，检测到的AuroSS与人类视觉感知一致。根据获得的AuroSS，可以自动估计极光弧的方向和长度。通过浏览从黄昏到黎明的弧线方向的时间变化，我们可以获得YRS极光活动的天气观测。