Target tracking based on the UAV platform is difficult to avoid the problem of large-scale variation. Due to the large change in the relative position between the UAV and the target, the size of the target in the video sequence will also change accordingly, resulting in poor tracking accuracy and low success rate. In order to solve the challenge of large-scale variation, based on the Siamese series of target tracking algorithms, the author proposes two improved methods to optimize the tracking frame and update the template. The optimization process is supplemented by updating the observation model to make it better adapt to the large-scale changes in the relative movement of the UAV and the target. Through the improvement of the target tracking algorithm based on the Siamese network, the target under large-scale transformation can be effectively tracked.
Target Tracking Under Large-Scale Variation Based on UAV Platform
Lect. Notes Electrical Eng.
International Conference on Autonomous Unmanned Systems ; 2022 ; Xi'an, China September 23, 2022 - September 25, 2022
Proceedings of 2022 International Conference on Autonomous Unmanned Systems (ICAUS 2022) ; Chapter : 209 ; 2244-2253
2023-03-10
10 pages
Article/Chapter (Book)
Electronic Resource
English
Towards large scale multi-target tracking
SPIE | 2014
|Towards large scale multi-target tracking [9085-32]
British Library Conference Proceedings | 2014
|Large Scale Simulation of a Distributed Target Tracking System
British Library Conference Proceedings | 2002
|Large-Scale Multiobject Emulation Platform for Noncooperative Target Missions in Space
DOAJ | 2024
|