1(Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China)2(Yunnan Xiaorun Technology Service Co.,Ltd.,Kunming 650500,China) 3(Yunnan Key Laboratory of Artifical Intelligence,Kunming University of Science and Technology,Kunming 650500,China) 4(Kunming Branch of the 705th Research Institute of China State ShipBuilding Co.,Ltd,Kunming 650102,China) 5(Yunnan Administration for Market Regulation,Kunming 650228,China)
Abstract：Aiming at the problem that the HOG feature map extracted from the local context area image in the kernel correlation filter target tracking algorithm can’t guarantee the accuracy of traget tracking in complex environments.A target tracking algorithm combining kernel correlation filter and siamese network is proposed.Firstly,extracting the HOG feature map to establish a correlation filter template in the first frame input image,and simultaneously extracting target area image feature map through siamese network.Then if the number of the input image frame in subsequent frames is not a multiple of five,extracting the affine transformation HOG feature map,otherwise extracting serach area image feature map through siamese network.Finally,according to the result of occlusion process to adaptively obtain the target position and update model and the final correlation filter template.Simulation results show that the algorithm in this paper has a tracking rate that meets the requirements of real-time tracking on the premise of ensuring traget tracking accuracy.
2021, Vol. 42 
