Unmanned Aerial Vehicle(UAV)target tracking tasks are often suffer from small target size,large scale variance and frequent viewpoint change.To address these issues,in this paper,an UAV target tracking algorithm based on high-resolution siamese network is proposed.Firstly,a high-resolution network is improved as the feature extraction backbone network(Lite-high resolution network,L-HRNet),and a dynamic multi-template strategy is used to mine the inter-frame information of the video.Secondly,a multi-frame feature fusion module is constructed to obtain fusion features that are beneficial to target localization.Finally,an anchor-free strategy is selected to locate the target position and obtain accurate tracking results.The experimental results show that the success rate and accuracy of the proposed algorithm are 66.0%and 84.7%on DTB70 dataset,65.7%and 84.3%on UAV123 dataset respectively,which improves the target tracking performance effectively.
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