A new method for online tracking of multi-armored targets
The realization of multi-armored target tracking plays a vital role in cooperative tracking and strike,and the realization of multi-armored target tracking needs to solve the problems of occlusion,in-terspersed and constantly changing target scales between targets.Therefore,an online multi-armored tar-get tracking method based on visual-attention Gabor filter is proposed to achieve the tracking of multi-armored targets in the ground battlefield.A visual-attention Gabor filter branch is constructed to enhance detection by simulating the retinal structure.By introducing temporal information,the problem of target occlusion is solved by using an online learned target-specific convolutional neural network.What is more important,a multi-armored target tracking dataset is constructed by means of actual shooting and down-loading from the internet,and the current mature multi-target tracking methods are compared with the method proposed in this paper through experiment.The experiments show that the method in this paper not only has excellent tracking performance,but also can meet the actual application requirements.
NETL
NSTL
万方数据
维普
