首页|基于自适应尺度变换与特征融合的目标跟踪

基于自适应尺度变换与特征融合的目标跟踪

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针对传统核相关滤波算法在目标被遮挡或发生运动模糊时跟踪效果不佳的情况,为了达到运动目标的实时稳定跟踪,提高跟踪系统的精度和成功率,提出一种基于核相关滤波的具有尺度自适应和特征融合的目标跟踪方法.首先在特征提取过程中,通过在原有的方向梯度直方图特征后添加颜色特征来提高目标特征的识别能力,即将HOG特征与CN特征相融合,然后构建尺度金字塔来进行尺度估计以达到目标的尺度自适应,最后通过多峰值检测机制实现模型的更新.通过在OTB2015 数据集中进行测试,算法的精确率和成功率有了进一步提升,该算法能够准确地识别出目标,并对目标进行有效跟踪.
Target tracking based on adaptive scale transform and feature fusion
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.

target tracking technologycorrelation filteringfeature fusionscalingmulti peak detection

牛思杰、汪志锋、朱晶晶

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上海第二工业大学,上海 201209

目标跟踪技术 相关滤波 特征融合 尺度变化 多峰值检测

2024

指挥控制与仿真
中国船舶重工集团公司 第七一六研究所

指挥控制与仿真

CSTPCD
影响因子:0.309
ISSN:1673-3819
年,卷(期):2024.46(4)
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