Unmanned Aerial Vehicle Tracking

Unmanned Aerial Vehicle (UAV) tracking focuses on reliably locating and following UAVs in diverse environments, often using computer vision techniques. Current research emphasizes improving the robustness and efficiency of tracking algorithms, particularly addressing challenges like motion blur, occlusion, low-light conditions, and GNSS-denied environments; popular approaches include Siamese networks, Vision Transformers, and correlation filters, often enhanced with techniques like contrastive learning and multi-modal sensor fusion. Advances in this field are crucial for numerous applications, including surveillance, autonomous navigation, and counter-UAV systems, driving the development of more accurate, efficient, and robust tracking solutions.