As simple feature and less information of infrared target lead to low tracking accuracy,a kernel correlation filtering algorithm based on gray and significant features fusion is proposed for aerial infrared target tracking.First of all,under the premise of ensuring enough target feature information,the larger target is compressed at different levels.Then,the extracted two-dimensional gray feature and saliency feature are spliced into three-dimensional features by page,and then the fusion features are used for kernel correlation filtering.The experimental results show that the proposed algorithm can adapt aerial infrared target tracking under a variety of environments,and the typical values of tracking accuracy and success rate reach 84.8% and 63.9% respectively.The average tracking speed reaches up to 125 frames per second,which reflects the good real-time.Therefore,the proposed algorithm can improve the tracking reliability and the real-time performance,and has a certain practical value.
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郑武兴,王春平,付强,徐艳.融合灰度与显著性特征的空中红外目标跟踪[J].激光与红外,2018,48(3):338~342 ZHENG Wu-xing, WANG Chun-ping, FU Qiang, XU Yan. Aerial infrared target tracking based on gray and saliency features fusion[J]. LASER & INFRARED,2018,48(3):338~342