指挥控制与仿真2024，Vol.46Issue(4)：82-87,6.DOI:10.3969/j.issn.1673-3819.2024.04.011
基于自适应尺度变换与特征融合的目标跟踪
Target tracking based on adaptive scale transform and feature fusion
摘要
Abstract
In order to achieve real-time stable tracking of moving targets and improve the accuracy and success rate of the tracking system,a kernel correlation filtering-based target tracking method with scale adaptation and feature fusion is pro-posed to address the situation that the traditional kernel correlation filtering algorithm does not track well when the target is obscured or motion blurred.Firstly,in the feature extraction process,color features are added after the original directional gradient histogram features to improve the recognition capability of target features,that is HOG features are fused with CN features,then a scale pyramid is constructed to perform scale estimation to achieve scale adaptation of the target,and finally the model is updated through a multi-peak detection mechanism.Through testing on the OTB2015 dataset,the accuracy and success rate of the algorithm has been further improved,and the algorithm is able to accurately identify targets and track them effectively.关键词
目标跟踪技术/相关滤波/特征融合/尺度变化/多峰值检测Key words
target tracking technology/correlation filtering/feature fusion/scaling/multi peak detection分类
信息技术与安全科学引用本文复制引用
牛思杰,汪志锋,朱晶晶..基于自适应尺度变换与特征融合的目标跟踪[J].指挥控制与仿真,2024,46(4):82-87,6.
