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尺度自适应核相关滤波目标跟踪

Scale Adaptive Kernel Correlation Filtering for Target Tracking

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摘要

针对传统跟踪方法难以实时准确适应目标尺度变化这一问题, 基于核相关滤波跟踪框并采用尺度估计方法, 提出一种自适应尺度的目标跟踪算法。对正则化最小二乘分类器进行求解, 获得滤波模板, 并对候选样本进行检测, 估计出目标的位置; 利用尺度估计方法, 在已确定目标位置处根据前一帧目标的大小对当前帧目标尺度进行检测, 由最大的响应值确定当前帧目标的尺度; 根据遮挡检测机制, 在线更新目标和尺度模型参数。实验结果表明, 所提出的算法与其他跟踪算法中的最优者相比, 距离精度提高了17.12%, 成功率提高了10.77%; 在目标发生背景干扰、严重遮挡以及在光照、姿态和尺度变化等复杂场景下, 该算法仍具有较好的跟踪效果。

Abstract

Focusing on the issue that the traditional tracking method is difficult to adapt to the target scale variation in real time accurately, an adaptive scale target tracking algorithm based on kernel correlation filtering tracking framework, which adapts a scale estimation method, is proposed. Firstly, the regularized least squares classifier is used to obtain the filter template, and the position of the target is estimated by detecting the candidate samples. Then, the scale of current frame is determined based on the target size of the previous frame, and the scale samples are obtained by the maximum response value through the scale estimation method. Finally, the target and scale model parameters are updated online according to the occlusion detection mechanism. The experimental results show that the proposed algorithm improves the distance precision by 17.12% and the success rate by 10.77% as compared with the best of the other tracking algorithms. In complex scenes, such as background clutters, severe occlusion, and illumination, posture and scale variation, the proposed algorithm still has a good tracking performance.

Newport宣传-MKS新实验室计划
补充资料

中图分类号:TP391

DOI:10.3788/lop55.041501

所属栏目:机器视觉

基金项目:国家自然科学基金(61373126)

收稿日期:2017-09-13

修改稿日期:2017-10-20

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作者单位    点击查看

高美凤:江南大学轻工过程先进控制教育部重点实验室, 江苏 无锡 214122
张晓玄:江南大学轻工过程先进控制教育部重点实验室, 江苏 无锡 214122

联系人作者:张晓玄(1762248458@qq.com)

备注:高美凤(1963—), 女, 博士, 副教授, 硕士生导师, 主要从事图像处理、无线传感网定位技术方面的研究。gaojndx@163.com

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引用该论文

Gao Meifeng,Zhang Xiaoxuan. Scale Adaptive Kernel Correlation Filtering for Target Tracking[J]. Laser & Optoelectronics Progress, 2018, 55(4): 041501

高美凤,张晓玄. 尺度自适应核相关滤波目标跟踪[J]. 激光与光电子学进展, 2018, 55(4): 041501

被引情况

【1】马晓虹. 目标跟踪中增强梯度阈值的更新方法. 激光与光电子学进展, 2018, 55(6): 61502--1

【2】何雪东,周盛宗. 快速尺度自适应核相关滤波目标跟踪算法. 激光与光电子学进展, 2018, 55(12): 121501--1

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