摘要
随着红外探测器性能的不断提升,红外目标跟踪在智能安防等领域的应用越来越广泛。然而红外图像分辨率较低,依赖其进行目标跟踪仍然是一个制约相关应用发展的难题。针对红外图像分辨率低的特点,以多域网络为模型算法框架,结合目标运动过程中的尺寸变化特点,提出了一种基于多域网络的红外目标跟踪算法。为了评估算法性能,分别在VOT-TIR2016数据库和AMCOM红外数据上进行了实验。实验结果表明,目标尺度预测机制能够显著提高算法的跟踪精度。
With the continuous improvement of infrared detector performance,infrared target tracking is more and more widely used in intelligent security and other fields.However,it is still a difficult problem to rely on infrared image for target tracking due to the low resolution of infrared image.In view of the low resolution of infrared image,combining with the characteristics of size change in the process of target movement,a multi-domain network based infrared target tracking algorithm is proposed,which is based on the multi-domain network.To assess the algorithm performance,experiments are conducted on the VOT-TIR2016 database and AMCOM infrared data,respectively.Experimental results show that the target scale prediction mechanism can significantly improve the tracking accuracy of the algorithm.
作者
孙明杰
周林
顾金玲
李培庚
SUN Mingjie;ZHOU Lin;GU Jinling;LI Peigeng(Air and Missile Defense College, Air Force Engineering University, Xi’an 710051, China;Unit 32272 of the PLA, Lanzhou 730010, China;Unit 95169 of the PLA, Nanning 530031, China)
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2021年第5期1176-1183,共8页
Systems Engineering and Electronics
基金
陕西省自然科学基础研究计划(2019JQ-708)资助课题。
关键词
多域网络
目标跟踪
红外成像
深度学习
multi-domain network
target tracking
infrared imaging
deep learning