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高效的多特征自适应相关滤波跟踪器
引用本文:张思贤,杨艺,张猛,米鹏博. 高效的多特征自适应相关滤波跟踪器[J]. 系统仿真学报, 2022, 34(8): 1864-1873. DOI: 10.16182/j.issn1004731x.joss.21-0274
作者姓名:张思贤  杨艺  张猛  米鹏博
作者单位:1.西安交通大学 机械结构强度与振动国家重点实验室,陕西 西安 7100492.西安交通大学 航天航空学院,陕西 西安 710049
基金项目:国家自然科学基金(61671370);中国博士后科学基金(2016M592790);中央高校基本科研业务费专项资金(xjj2016066);陕西省博士后基金(2016BSHEDZZ46)
摘    要:针对基于手工特征的相关滤波跟踪器在快速变形、背景杂乱等挑战性跟踪场景效果不佳的问题,在Staple跟踪器的基础上提出了一种新型的相关滤波跟踪器。结合方向梯度直方图特征与颜色命名特征构建了目标外观模型,增强其对快速变形以及背景杂乱等场景的鲁棒性;设计了自适应评分函数对2种特征进行融合,得到更具有鉴别性的特征;针对不同的特征分别提出了在线更新策略以减小训练过拟合与模型漂移。实验结果表明:该跟踪器在跟踪的准确性与实时性上均有着优良表现。

关 键 词:目标跟踪  相关滤波  自适应评分函数  颜色命名特征  在线更新
收稿时间:2021-03-31

An Efficient Tracker via Multi-feature Adaptive Correlation Filter
Sixian Zhang,Yi Yang,Meng Zhang,Pengbo Mi. An Efficient Tracker via Multi-feature Adaptive Correlation Filter[J]. Journal of System Simulation, 2022, 34(8): 1864-1873. DOI: 10.16182/j.issn1004731x.joss.21-0274
Authors:Sixian Zhang  Yi Yang  Meng Zhang  Pengbo Mi
Affiliation:1.State Key Laboratory for Strength and Vibration of Mechanical Structure, Xi'an Jiaotong University, Xi'an 710049, China2.School of Aerospace, Xi'an Jiaotong University, Xi'an 710049, China
Abstract:Aiming at the low tracking effect of the correlation filters tracker based on manual features in challenging scenes of rapid deformation and background clutter, a new correlation filter tracker based on Staple tracker is proposed. An appearance model based on HOG features and color-naming features is built to enhance the robustness to the challenging scenes of rapid deformation and background clutter. A self-adjust evaluation function is designed to merge the two kinds of feature information and a more discriminative feature is obtained. The novel online update strategies to reduce the training over-fitting and model drift for different features are proposed. The tracker shows excellent performance in accuracy and real-time capability on OTB2015 benchmark.
Keywords:object tracking  correlation filter  self-adjust evaluation function  color-naming feature  online update  
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