基于自适应Siamese网络的无人机目标跟踪算法

doi:10.7527/S1000-6893.2019.23423

Abstract

Abstract: UAVs have been widely used in military and civilian applications. Target tracking is one of the key technologies for UAV applications. Aiming at the problem that the target is prone to deformation and occlusion during the tracking process of the UAV, a target tracking algorithm for UAV based on adaptive Siamese network is proposed. Firstly, using two convolution networks, a 5-layer Siamese network is constructed. The target location is obtained by convolving the template features with the current frame image features. Secondly, the Gaussian mixture model is used to model the previous prediction results and establish the target template library. Thirdly, the most reliable target template is selected from the template library to update the matching template of the Siamese network, so that the Siamese network can adapt to the target. Finally, a regression model is introduced to further pinpoint the target location and reduce the impact of background on network performance. The results show that the algorithm effectively reduces the influence of deformation and occlusion on tracking performance and are highly accurate.

Key words: UAV, target tracking, Siamese network, template matching, adaptive update

CLC Number:

V279
TP391

LIU Fang, YANG Anzhe, WU Zhiwei. Adaptive Siamese network based UAV target tracking algorithm[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(1): 323423-323423.

References 29

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Adaptive Siamese network based UAV target tracking algorithm

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