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Learning adaptive spatial–temporal regularized correlation filters for visual tracking

Jianwei Zhao, Yangxiao Li, Zhenghua Zhou
2021 IET Image Processing  
This paper proposes an effective tracking method, named adaptive spatial-temporal regularized correlation filter (ASTRCF) tracker, based on the popular adaptive spatially regularized correlation filter  ...  take advantage of the relation of correlation filters in the last frame and the current frame for addressing the complex cases, such as occlusion, and fast motion.  ...  This paper proposes a novel CF-based tracker, named an adaptive spatial-temporal regularized correlation filter (ASTRCF) tracker, by introducing the temporal regularization term in the appearance model  ... 
doi:10.1049/ipr2.12150 fatcat:dcx6cmuaknggvpydtcygazcdqi

Correlation Tracking via Spatial-Temporal Constraints and Structured Sparse Regularization

Dan Tian, Shouyu Zang, Binbin Tu
2021 IEEE Access  
To solve this problem, we present a spatial-temporal constraints and structured sparse regularization based formulation for correlation tracking.  ...  [9] learn temporal regularized correlation filters to adapt to the change of the tracking scenes. Huang et al.  ... 
doi:10.1109/access.2021.3086821 fatcat:nrjp7qxlirazzltbjouq7tqdaq

Visual Tracking via Adaptive Spatially-Regularized Correlation Filters

Kenan Dai, Dong Wang, Huchuan Lu, Chong Sun, Jianhua Li
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
First, this adaptive spatial regularization scheme could learn an effective spatial weight for a specific object and its appearance variations, and therefore result in more reliable filter coefficients  ...  In this work, we propose a novel adaptive spatiallyregularized correlation filters (ASRCF) model to simultaneously optimize the filter coefficients and the spatial regularization weight.  ...  This paper is supported in part by National Natural Science Foundation of China Nos. 61872056, 61771088, 61751212, 61725202 and 61829102, and in part by the Fundamental Research Funds for the Central Universities  ... 
doi:10.1109/cvpr.2019.00480 dblp:conf/cvpr/Dai0LSL19 fatcat:yi44ojlcz5bnzewydnvy4jgwsi

Learning Temporal Regularized Correlation Filter Tracker with Spatial Reliable Constraint

Lei Pu, Xinxi Feng, Zhiqiang Hou
2019 IEEE Access  
The advantage of correlation filter-based tracking methods is mainly attributed to powerful features and effective online filter learning.  ...  INDEX TERMS Visual tracking, correlation filter, convolutional neural network, spatial constraint, temporal regularization.  ...  CNN BASED CORRELATION FILTER For robust tracking, more discriminative features are widely used.  ... 
doi:10.1109/access.2019.2922416 fatcat:mzli7ni3bfes5bb6f7rstypkvy

Learning an Orientation and Scale Adaptive Tracker with Regularized Correlation Filters

Ke Tan, Zhenzhong Wei
2019 IEEE Access  
Spatial and temporal constraints are very important for correlation filter (CF)-based trackers.  ...  To address the issue, we propose a novel Orientation and Scale adaptive tracker with Regularized Correlation Filters (OSRCF) for visual tracking.  ...  TRACKING WITH OSRCF TRACKER Based on the target-region-based spatially and temporally regularized filter and the orientation and scale adaptive scheme, we propose a OSRCF tracker.  ... 
doi:10.1109/access.2019.2912527 fatcat:ha2xyn7ljnayvbnszj4aufalpi

Second-Order Spatial-Temporal Correlation Filters for Visual Tracking

Yufeng Yu, Long Chen, Haoyang He, Jianhui Liu, Weipeng Zhang, Guoxia Xu
2022 Mathematics  
Discriminative correlation filters (DCFs) have been widely used in visual object tracking, but often suffer from two problems: the boundary effect and temporal filtering degradation.  ...  To deal with these issues, many DCF-based variants have been proposed and have improved the accuracy of visual object tracking.  ...  Acknowledgments: We greatly thank the Reviewers and Editors for the insightful comments and suggestions. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/math10050684 fatcat:5aqumuqzfnefrfty3wmmjh64nm

Adaptive Spatial-Temporal Regularization for Correlation Filters Based Visual Object Tracking

Fei Chen, Xiaodong Wang
2021 Symmetry  
In this paper, we propose a novel framework that employs adaptive spatial regularization and temporal regularization to learn reliable filters in both spatial and temporal domains for tracking.  ...  Recently, Discriminative Correlation Filters (DCF) have shown excellent performance in visual object tracking.  ...  [13] proposed kernelized correlation filters (KCF) based on linear and kernel ridge regression for fast visual object tracking.  ... 
doi:10.3390/sym13091665 fatcat:ybgcts4xybbbfjzbfczmwrzfpq

Railway Foreign Object Tracking Based on Correlation Filtering of Optimized Regularization Model

Tao Hou, Yannan Chen, Caiwen Bao, Yuhu Chen
2021 Journal of Applied Science and Engineering  
, fully excavate the expressive ability of deep space features, and a foreign object tracking algorithm based on correlation filtering with depth space and time perception regularization is put forward  ...  Aiming at problems such as the untrustworthy association between spatial regularization weight and intrusive foreign object in complex railway scenes, as well as the degradation of correlation filter model  ...  In order to better solve the boundary effect problem, spatial-variation regularization correlation filters [10] , the correlation filtering tracking algorithm based on adaptive spatial regularization  ... 
doi:10.6180/jase.202204_25(2).0015 doaj:cc829408d0a14d58aff3eaf7b38fad5d fatcat:pzv3odoibnh4fap7xdlvlvaq34

STResNet_CF Tracker: The deep spatiotemporal features learning for correlation filter based robust visual object tracking

Zhengyu Zhu, Bing Liu, Yunbo Rao, Qiao Liu, Rui Zhang
2019 IEEE Access  
This paper presents a novel method for visual object tracking based on spatiotemporal feature combined with correlation filters.  ...  Finally, our spatiotemporal fusion feature from STResNet appearance model is incorporated into the correlation filter for robust visual object tracking.  ...  TRACKERS BASED ON CORRELATION FILTER Since 2010, a number of Correlation Filter (CF) based trackers have been proposed that can tolerate variations in object appearance and track object through complex  ... 
doi:10.1109/access.2019.2903161 fatcat:uas76gauobcspkjwvuvy6wpevi

Learning Augmented Memory Joint Aberrance Repressed Correlation Filters for Visual Tracking

Yuanfa Ji, Jianzhong He, Xiyan Sun, Yang Bai, Zhaochuan Wei, Kamarul Hawari bin Ghazali
2022 Symmetry  
Based on the background-aware correlation filter (BACF), we introduced adaptive spatial regularity to mitigate the boundary effect.  ...  With its outstanding performance and tracking speed, discriminative correlation filters (DCF) have gained much attention in visual object tracking, where time-consuming correlation operations can be efficiently  ...  [33] proposed the semantic-aware spatial regularization correlation filter by using spatial semantic maps to model regularization and feature selection.  ... 
doi:10.3390/sym14081502 fatcat:n644zistrjcvfkavz4kqd7vrai

Adaptive Learning Rate for Visual Tracking Using Correlation Filters

C.S. Asha, A.V. Narasimhadhan
2016 Procedia Computer Science  
Recently correlation filter based video tracking gained popularity due to its efficiency and high frame rate.  ...  This method uses integral channel features in correlation filter framework with adaptive learning rate to efficiently track the object.  ...  For further reference, it is named as integral channel feature based adaptive learning correlation tracking (ICF-ALC).  ... 
doi:10.1016/j.procs.2016.06.023 fatcat:ce7mrmtvpzfbtokfhcxqdy3dp4

Learning Padless Correlation Filters for Boundary-Effect Free Tracking

Dongdong Li, Gongjian Wen, Yangliu Kuai, Fatih Porikli
2018 IEEE Sensors Journal  
Recently, discriminative correlation filters (DCFs) have achieved enormous popularity in the tracking community due to high accuracy and beyond real-time speed.  ...  Among different DCF variants, spatially regularized discriminative correlation filters (SRDCFs) demonstrate excellent performance in suppressing boundary effects induced from circularly shifted training  ...  Second, the learned correlation filter is a trade-off between the desired correlation response and spatial regularization, and thus SRDCF cannot guarantee the filter values are zero outside of object bounding  ... 
doi:10.1109/jsen.2018.2861912 fatcat:yrud7uixufaaheitsk7fg4ozly

Adaptive Context-Aware and Structural Correlation Filter for Visual Tracking

Bin Zhou, Tuo Wang
2019 Applied Sciences  
In this paper, we presented an adaptive context-aware (CA) and structural correlation filter for tracking. Firstly, we propose a novel context selecting strategy to obtain negative samples.  ...  Accurate visual tracking is a challenging issue in computer vision. Correlation filter (CF) based methods are sought in visual tracking based on their efficiency and high performance.  ...  In this paper, we propose an adaptive context-aware and structural correlation filter for object tracking.  ... 
doi:10.3390/app9071338 fatcat:b4q5bx7kpfeojb6bwm4vmxou5q

Learning Spatial–Temporal Background-Aware Based Tracking

Peiting Gu, Peizhong Liu, Jianhua Deng, Zhi Chen
2021 Applied Sciences  
Discriminative correlation filter (DCF) based tracking algorithms have obtained prominent speed and accuracy strengths, which have attracted extensive attention and research.  ...  In this paper, a spatial–temporal regularization module based on BACF (background-aware correlation filter) framework is proposed, which is performed by introducing a temporal regularization to deal effectively  ...  Acknowledgments: The authors would like to thank all of the reviewers for their constructive comments. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app11188427 fatcat:ecwy6lflg5bkppm2byyanuoquy

Adaptive Weight Collaborative Complementary Learning for Robust Visual Tracking

2019 KSII Transactions on Internet and Information Systems  
Discriminative correlation filter (DCF) based tracking algorithms have recently shown impressive performance on benchmark datasets.  ...  Secondly, to enhance the discriminative power of the learned template model, the spatial regularization is introduced in the learning stage to penalize the objective boundary information corresponding  ...  Fast Discriminative Multi-Scale Estimate Method Adaptive multi-scale correlation filter When tracking the target in a series of images, the size of the target is varying all the time with the change  ... 
doi:10.3837/tiis.2019.01.018 fatcat:yenwet23ije65nxwxjpgro277q
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