Single object tracking (SOT) in satellite video (SV) enables the continuous acquisition of position and range information of an arbitrary object, showing promising value in remote sensing applications. However, existing trackers and datasets rarely focus on the SOT of oriented objects in SV. To bridge this gap, this article presents a comprehensive review of various tracking paradigms and frameworks covering both the general video and satellite video domains and subsequently proposes the oriented object tracking benchmark (OOTB) to advance the field of visual tracking. OOTB contains 29,890 frames from 110 video sequences, covering common satellite video object categories including car, ship, plane, and train. All frames are manually annotated with oriented bounding boxes, and each sequence is labeled with 12 fine-grained attributes. Additionally, a high-precision evaluation protocol is proposed for comprehensive and fair comparisons of trackers. To validate the existing trackers and explore frameworks suitable for SV tracking, we benchmark 33 state-of-the-art trackers totaling 58 models with different features, backbones, and tracker tags. Finally, extensive experiments and insightful thoughts are also provided to help understand their performance and offer baseline results for future research. OOTB is available at .

中文翻译：

---

卫星视频单目标跟踪：系统回顾和定向目标跟踪基准

卫星视频（SV）中的单目标跟踪（SOT）能够连续获取任意目标的位置和范围信息，在遥感应用中显示出有希望的价值。然而，现有的跟踪器和数据集很少关注 SV 中定向对象的 SOT。为了弥补这一差距，本文对涵盖通用视频和卫星视频领域的各种跟踪范例和框架进行了全面回顾，并随后提出了面向对象跟踪基准（OOTB）以推进视觉跟踪领域的发展。 OOTB 包含来自 110 个视频序列的 29,890 帧，涵盖常见的卫星视频对象类别，包括汽车、船舶、飞机和火车。所有帧均使用定向边界框手动注释，每个序列均标有 12 个细粒度属性。此外，还提出了高精度评估协议，以对跟踪器进行全面、公平的比较。为了验证现有的跟踪器并探索适合 SV 跟踪的框架，我们对 33 个最先进的跟踪器进行了基准测试，总计 58 个具有不同功能、骨干网和跟踪器标签的模型。最后，还提供了广泛的实验和富有洞察力的想法，以帮助了解其性能并为未来的研究提供基线结果。 OOTB 可在 获取。