基于样本可靠性的时空正则化自适应相关滤波目标跟踪  

Spatiotemporal Regularized Adaptive Correlation Filtering Target Tracking Based on Sample Reliability

作　　者：陈中意 陶洋[1] CHEN Zhong-yi;TAO Yang(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[1]重庆邮电大学通信与信息工程学院,重庆400065

出　　处：《小型微型计算机系统》2023年第9期2038-2044,共7页Journal of Chinese Computer Systems

基　　金：国家重点研发计划项目(2019YFB2102001)资助;国家自然科学基金项目(61801072)资助;重庆市技术创新与应用发展专项项目(cstc2020jscx-msxmX0178)资助.

摘　　要：针对基于时空正则化相关滤波的目标跟踪算法,在解决边界效应时引入的空间权重矩阵无法自适应目标变化和时间正则项超参数固定无法自适应更新,容易引入背景噪声导致模型漂移等问题,提出了一种基于样本可靠性的时空正则化自适应相关滤波目标跟踪算法.首先,该算法通过图像的空间可靠性自适应调节空间权重参考矩阵,自适应空间正则项结合空间权重参考矩阵在一定程度上降低了边界效应的影响.然后,使用前后两帧响应图的变化程度确定时间正则项的超参数参考值,避免模型发生突变造成跟踪漂移问题.最后本文通过交替方向乘子法(ADMM)迭代求解目标函数,保证算法的运行效率.本文算法在OTB2013与OTB2015公开数据上进行了相关实验,大量实验表明:本文算法能够较好的处理复杂环境下的目标跟踪问题,其距离精度和跟踪成功率优于其他对比算法.Aiming at the target tracking algorithm based on spatio-temporal regularization correlation filtering,the spatial weight matrix introduced when solving boundary effects cannot adapt to target changes and the time regular term hyperparameters are fixed and cannot be adaptively updated.It is easy to introduce background noise and cause model drift.A target tracking algorithm with spatiotemporal regularization and adaptive correlation filtering based on sample reliability is proposed.First,the algorithm adjusts the spatial weight reference matrix adaptively through the spatial reliability of the image,and the adaptive spatial regularization term combined with the spatial weight reference matrix reduces the influence of the boundary effect to a certain extent.Then,the change degree of the response graphs of the two frames before and after is used to determine the hyperparameter reference value of the time regular term,so as to avoid the tracking drift problem caused by the sudden change of the model.Finally,this paper uses the Alternating Direction Multiplier Method(ADMM)to solve the objective function iteratively to ensure the efficiency of the algorithm.The algorithm in this paper has carried out related experiments on the public data of OTB2013 and OTB2015.A large number of experiments show that the algorithm in this paper can better deal with target tracking problems in complex environments,and its range accuracy and tracking success rate are better than other comparison algorithms.

关 键 词：目标跟踪 相关滤波 正则化自适应 空间可靠性 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]