激光与光电子学进展, 2019, 56 (22): 221503, 网络出版: 2019-11-02   

基于前景感知的时空相关滤波跟踪算法 下载: 929次

Foreground-Aware Based Spatiotemporal Correlation Filter Tracking Algorithm
虞跃洋 1,2,3,4,5,*史泽林 1,2,3,4,5刘云鹏 2,3,4,5
作者单位
1 中国科学技术大学信息科学技术学院, 安徽 合肥 230026
2 中国科学院沈阳自动化研究所, 辽宁 沈阳 110016
3 中国科学院机器人与智能制造创新研究院, 辽宁 沈阳 110016
4 中国科学院光电信息处理重点实验室, 辽宁 沈阳 110016
5 辽宁省图像理解与视觉计算重点实验室, 辽宁 沈阳 110016
摘要
针对长时目标跟踪中目标背景混杂、遮挡、目标移出视野导致的跟踪失败问题,基于空间正则化相关滤波(SRDCF),提出一个基于前景感知的时空相关滤波算法。首先,提出前景感知相关滤波方法,使得滤波器能够准确地把目标前景区域和背景区域进行区分;然后,把前景感知滤波器加入时间正则项中,使具有时空正则化功能的滤波器始终保持在一个低维的判别流形上;同时,采用交替方向乘子法(ADMM)求解,使得跟踪方法在传统特征的表达上能实现实时性;最后,确定目标重检测器的激活阈值,利用候选区域方法结合相关滤波方法实现重检测,达到长时跟踪的目的。在标准数据集OTB-2013上分别利用传统特征和卷积特征进行实验,并与SRDCF相比,跟踪平均成功率分别提高了5.6%和7%。本文算法针对目标背景模糊、旋转、遮挡和移出视野等情况,具有较强的稳健性。
Abstract
In this study, we propose a foreground-aware based spatiotemporal correlation filter algorithm based on the spatially regularized discriminative correlation filter (SRDCF) to deal with long-term object tracking failures caused by background clutter, occlusions, and out-of-view objects. Initially, a foreground-aware correlation filtering algorithm is proposed to distinguish the foreground and background of the object accurately. Subsequently, the foreground-aware filter is added to the time regularization term to keep the filter with spatiotemporal regularization function in a low-dimensional discriminative manifold. Simultaneously, the solution based on the alternating direction method of multipliers (ADMM) is conducted to achieve real-time operation of the tracking method in the traditional feature expression. Finally, the activation threshold of object re-detector is determined, and the candidate region method combined with correlation filtering method is used to achieve re-detection, so as to achieve the purpose of long-term tracking. We conduct experiments using traditional and convolutional features with respect to the OTB2013 standard dataset and observe that the average success rates of tracking are 5.6% and 7% higher, respectively, when compared with that of SRDCF. Therefore, the proposed approach is a robust method for handling background blur, rotations, occlusions, and out-of-view objects.

虞跃洋, 史泽林, 刘云鹏. 基于前景感知的时空相关滤波跟踪算法[J]. 激光与光电子学进展, 2019, 56(22): 221503. Yueyang Yu, Zelin Shi, Yunpeng Liu. Foreground-Aware Based Spatiotemporal Correlation Filter Tracking Algorithm[J]. Laser & Optoelectronics Progress, 2019, 56(22): 221503.

本文已被 3 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!