With the development of aviation technology, UAV technology has gradually become a research hotspot in the aviation field, and it plays a vital role in civil and military construction. Target detection and tracking of aerial video is a key technology for UAV reconnaissance, disaster relief, enemy monitoring, and military strikes. This paper studies the YOLOv3 target detection algorithm and SiamMask target tracking algorithm based on deep learning, and compares these algorithms Based on the situation of long aerial photography distance and small target, the algorithm is improved and fused to realize rapid target identification and tracking under UAV aerial photography. At the same time, in order to simplify the model and accelerate the speed of model training and reasoning, the simplification of the tracking algorithm model is studied. Finally, an aerial photography experiment was conducted in an outdoor environment to verify the effectiveness of the UAV target detection and tracking algorithm.
UAV Aerial Photography Target Detection and Tracking Based on Deep Learning
Lect. Notes Electrical Eng.
Proceedings of the 5th China Aeronautical Science and Technology Conference ; Kapitel : 42 ; 426-438
2021-11-02
13 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Improved YOLOv7 Target Detection Algorithm Based on UAV Aerial Photography
DOAJ | 2024
|3D AERIAL PHOTOGRAPHY SYSTEM EDITABLE 3D TARGET IMAGE OF DIGITAL AERIAL PHOTOGRAPHY INFORMATION
Europäisches Patentamt | 2021
|AERIAL PHOTOGRAPHY SYSTEM, AERIAL PHOTOGRAPHY METHOD, AND AERIAL PHOTOGRAPHY PROGRAM
Europäisches Patentamt | 2024
|