Learning Dual-Domain Calibration and Distance-Driven Correlation Filter:A Probabilistic Perspective for UAV Tracking  

作　　者：Taiyu Yan Yuxin Cao Guoxia Xu Xiaoran Zhao Hu Zhu Lizhen Deng 

机构地区：[1]Jiangsu Province Key Lab on Image Processing and Image Communication,Nanjing University of Posts and Telecommunications,Nanjing,China [2]School of Computer Science,Qufu Normal University,Qufu,China [3]National Engineering Research Center of Communication and Network Technology,Nanjing University of Posts and Telecommunications,Nanjing,China

出　　处：《Computers, Materials & Continua》2023年第12期3741-3764,共24页计算机、材料和连续体（英文）

基　　金：supported by the National Natural Science Foundation of China under Grant 62072256;Natural Science Foundation of Nanjing University of Posts and Telecommunications(Grant Nos.NY221057,NY220003).

摘　　要：Unmanned Aerial Vehicle(UAV)tracking has been possible because of the growth of intelligent information technology in smart cities,making it simple to gather data at any time by dynamically monitoring events,people,the environment,and other aspects in the city.The traditional filter creates a model to address the boundary effect and time filter degradation issues in UAV tracking operations.But these methods ignore the loss of data integrity terms since they are overly dependent on numerous explicit previous regularization terms.In light of the aforementioned issues,this work suggests a dual-domain Jensen-Shannon divergence correlation filter(DJSCF)model address the probability-based distance measuring issue in the event of filter degradation.The two-domain weighting matrix and JS divergence constraint are combined to lessen the impact of sample imbalance and distortion.Two new tracking models that are based on the perspectives of the actual probability filter distribution and observation probability filter distribution are proposed to translate the statistical distance in the online tracking model into response fitting.The model is roughly transformed into a linear equality constraint issue in the iterative solution,which is then solved by the alternate direction multiplier method(ADMM).The usefulness and superiority of the suggested strategy have been shown by a vast number of experimental findings.

关 键 词：Dual-domain weighting distance measure correlation filter ADMM 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]