基于高分辨率孪生网络的无人机目标跟踪算法

doi:10.13229/j.cnki.jdxbgxb.20220790

Abstract

Abstract:

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.

Key words: computer vision, target tracking, unmanned aerial vehicle, high-resolution siamese network, multi-frame feature

CLC Number:

TP391.4

Dian-wei WANG,Chi ZHANG,Jie FANG,Zhi-jie XU. UAV target tracking algorithm based on high resolution siamese network[J].Journal of Jilin University(Engineering and Technology Edition), 2024, 54(5): 1426-1434.

Figures/Tables 10

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算法	成功率	精确率
SiamFC	0.487	0.738
SiamRPN	0.588	0.790
DaSiamRPN	0.610	0.796
SiamRPN++	0.614	0.800
SiamCAR	0.596	0.802
SiamBAN	0.643	0.834
本文	0.660	0.847

算法	低分辨率		尺度变化		视点改变		纵横比改变		相似物体		全遮挡
算法	S	P	S	P	S	P	S	P	S	P	S	P
SiamFC	0.346	0.719	0.476	0.697	0.479	0.686	0.436	0.661	0.466	0.706	0.306	0.571
SiamRPN	0.400	0.616	0.544	0.752	0.608	0.779	0.536	0.724	0.487	0.682	0.349	0.565
DaSiamRPN	0.411	0.663	0.560	0.754	0.563	0.753	0.537	0.739	0.517	0.747	0.379	0.633
SiamRPN++	0.433	0.666	0.578	0.775	0.637	0.833	0.544	0.756	0.541	0.740	0.354	0.582
SiamCAR	0.465	0.693	0.605	0.791	0.646	0.807	0.580	0.759	0.563	0.754	0.419	0.660
SiamBAN	0.472	0.719	0.613	0.813	0.639	0.824	0.591	0.796	0.566	0.777	0.418	0.671
本文	0.494	0.734	0.641	0.824	0.690	0.864	0.634	0.784	0.571	0.762	0.415	0.658

骨干网络	成功率/%	精确率/%
AlexNet	61.3	78.5
HRNet	63.0	81.7
L-HRNet	65.7	84.3

模板数量	成功率/%	精确率/%	帧率/（帧·s^-1）
1	61.5	80.6	46
2	64.8	83.0	34
3	65.7	84.3	29

UAV target tracking algorithm based on high resolution siamese network

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