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A dual-kernel-based tracking approach for visual target
2012
Science China Information Sciences
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A dual-kernel-based tracking approach for visual target is proposed in this paper. ...
By maximizing the linear approximation of objective function, a dual-kernel target location-shift relation from current location to a new location is induced. ...
Conclusions In the paper, a dual-kernel-based tracking (DKBT) approach is advocated. ...
doi:10.1007/s11432-011-4543-x
fatcat:fy557zdohver7aeb55yqnm2beq
Multi-template Scale-Adaptive Kernelized Correlation Filters
2015
2015 IEEE International Conference on Computer Vision Workshop (ICCVW)
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These drawbacks include an assumed fixed scale of the target in every frame, as well as, a heuristic update strategy of the filter taps to incorporate historical tracking information (i.e. simple linear ...
We validate the efficacy of our approach on two tracking datasets, VOT2014 and VOT2015. ...
Review of KCF Tracker KCF tracker has gained attention recently for achieving very impressive results on the visual tracking benchmark [24] , as well as, a high rank in the 2014 visual object tracking ...
doi:10.1109/iccvw.2015.83
dblp:conf/iccvw/BibiG15
fatcat:wlrylb2w4ndqzgb4nhvv5tjmtm
Object Tracking via Dual Linear Structured SVM and Explicit Feature Map
2016
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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Second, we approximate the intersection kernel for feature representations with an explicit feature map to further improve tracking performance. ...
In this paper, we present a simple yet efficient dual linear SSVM (DLSSVM) algorithm to enable fast learning and execution during tracking. ...
SSVM Based Tracking Analysis Although dual SSVMs with non-linear kernels usually perform better than ones with linear kernels for tracking, the training and detection processes are more complex. ...
doi:10.1109/cvpr.2016.462
dblp:conf/cvpr/NingYJZ016
fatcat:6lbze2z4afgqbeuoyselqewcwa
Deep Motion-Appearance Convolutions for Robust Visual Tracking
2019
IEEE Access
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In this paper, we propose a deep neural network for visual tracking, namely the Motion-Appearance Dual (MADual) network, which employs a dual-branch architecture, by using deep two-dimensional (2D) and ...
Sliding the 2D kernels on a frame and the 3D kernels on a frame cube synchronously enables a better hierarchical motion-appearance integration, and boosts the performance for the visual tracking task. ...
The main contributions of this paper are as follows: 1) We develop a new dual-branch network based on deep 2D and 3D convolutions for visual tracking, which enables a local-to-global integration of the ...
doi:10.1109/access.2019.2958405
fatcat:777v6zmdobgk5njbvsxsuv5x4i
Review on Kernel based Target Tracking for Autonomous Driving
2016
Journal of Information Processing
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This paper reviews the kernel theory adopted in target tracking of autonomous driving and makes a qualitative and quantitative comparison among several well-known kernel based methods. ...
The theoretical and experimental analysis allow us to conclude that the kernel based online subspace learning algorithm achieves a good trade-off between the stability and real-time processing for target ...
Kernel-based Tracking Template matching is a common approach for target tracking in video sequences. ...
doi:10.2197/ipsjjip.24.49
fatcat:yvyqgiug6nclzdn5jqailxmm7i
Real-Time Object Tracking via Adaptive Correlation Filters
2020
Sensors
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Herein, a real-time dual-template CFT for various challenge scenarios is proposed in this work. ...
Then, the dual-template is utilized based on the target response confidence. ...
fixed detection range, our approach can track the target successfully by utilizing the dual-template method. ...
doi:10.3390/s20154124
pmid:32722140
pmcid:PMC7435421
fatcat:355daiwgxndv3lmpokgmhsbl4y
A Scale Adaptive Kernel Correlation Filter Tracker with Feature Integration
[chapter]
2015
Lecture Notes in Computer Science
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Although the correlation filter-based trackers achieve the competitive results both on accuracy and robustness, there is still a need to improve the overall tracking capability. ...
In this paper, we presented a very appealing tracker based on the correlation filter framework. ...
old ; Ensure: The updated template for the tracked target, x; The updated dual space coefficient, α; The new position, pnew; 1: for every ti in S do 2: Sample the new patch z t i based on size tist and ...
doi:10.1007/978-3-319-16181-5_18
fatcat:dj6aksxo2ze6jippo73bsreote
Object tracking using a convolutional network and a structured output SVM
2017
Computational Visual Media
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In this paper, we present a novel method to model target appearance and combine it with structured output learning for robust online tracking within a tracking-by-detection framework. ...
To capture appearance variation during tracking, we propose a new strategy to update the target and background kernel pool. ...
The most popular approach based on the discriminative model casts tracking as a foreground and background separation problem, performing tracking by learning a classifier using multiple instance learning ...
doi:10.1007/s41095-017-0087-3
fatcat:4miqlot67vhpfc2idgyag4ka5a
Critical Overview of Visual Tracking with Kernel Correlation Filter
2021
Technologies
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This paper attempts to provide an understanding for one such correlation filter-based tracking technology, Kernelized Correlation Filter (KCF), which uses implicit properties of tracked images (circulant ...
Despite its strong practical potential in visual tracking, there is a need for an in-depth critical understanding of the method and its performance, which this paper aims to provide. ...
Consent for Publication: The picture materials quoted in this article have no copyright requirements, and the source, if applicable, has been indicated. ...
doi:10.3390/technologies9040093
fatcat:e7klqu6545dp5mqbozy4a5cbau
Kernalised Multi-resolution Convnet for Visual Tracking
[article]
2017
arXiv
pre-print
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Visual tracking is intrinsically a temporal problem. Discriminative Correlation Filters (DCF) have demonstrated excellent performance for high-speed generic visual object tracking. ...
Built upon their seminal work, there has been a plethora of recent improvements relying on convolutional neural network (CNN) pretrained on ImageNet as a feature extractor for visual tracking. ...
approach for visual tracking. ...
arXiv:1708.00577v1
fatcat:u6kz2j3yxrck5c2hlogdeqx4dy
Kernalised Multi-resolution Convnet for Visual Tracking
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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Visual tracking is intrinsically a temporal problem. Discriminative Correlation Filters (DCF) have demonstrated excellent performance for high-speed generic visual object tracking. ...
Built upon their seminal work, there has been a plethora of recent improvements relying on convolutional neural network (CNN) pretrained on ImageNet as a feature extractor for visual tracking. ...
approach for visual tracking. ...
doi:10.1109/cvprw.2017.278
dblp:conf/cvpr/WuZLZ17
fatcat:st46eaueuvf4xmmxhwyr2yoha4
Occlusion Aware Kernel Correlation Filter Tracker using RGB-D
[article]
2021
arXiv
pre-print
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We believe this work will set the basis for a better understanding of the effectiveness of kernel-based correlation filter trackers and to further define some of its possible advantages in tracking. ...
Unlike deep learning which requires large training datasets, correlation filter-based trackers like Kernelized Correlation Filter (KCF) uses implicit properties of tracked images (circulant matrices) for ...
Literature Review on RGB Based TrackersThe visual tracking community has been developing RGB based tracking for a long time. ...
arXiv:2105.12161v1
fatcat:kemrvvyqlba6dg3gwxnbcvfjdi
Learning Robust Gaussian Process Regression for Visual Tracking
2018
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
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In this paper, we propose a novel Gaussian Process Regression based tracker (GPRT) which is a conceptually natural tracking approach. ...
In addition, we present two efficient and effective update methods for our GPRT. Experiments are performed on two public datasets: OTB-2013 and OTB-2015. ...
is a conceptually natural tracking approach. ...
doi:10.24963/ijcai.2018/170
dblp:conf/ijcai/ZhengTW18
fatcat:zyjzrg5u45eshndqkjaxaa3vci
Manifold Regularized Correlation Object Tracking
2018
IEEE Transactions on Neural Networks and Learning Systems
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A block optimization strategy is further introduced to learn a manifold regularization-based correlation filter for efficient online tracking. ...
Experiments on two public tracking data sets demonstrate the superior performance of our tracker compared with the state-of-the-art tracking approaches. ...
Lately, correlation filter-based discriminative visual tracking approaches [6] , [8] have achieved great success. ...
doi:10.1109/tnnls.2017.2688448
pmid:28422697
fatcat:zi7m6rg2yjag5psjuqtnxc7cvu
Real-Time Visual Tracking: Promoting the Robustness of Correlation Filter Learning
[article]
2016
arXiv
pre-print
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Other Versions
This is a useful reference criterion in designing a robust correlation filter for visual tracking. ...
Correlation filtering based tracking model has received lots of attention and achieved great success in real-time tracking, however, the lost function in current correlation filtering paradigm could not ...
This also can be used as a criterion to design a robust correlation filter for visual tracking. ...
arXiv:1608.08173v2
fatcat:id7mgvgosbbkdheyy4llyse3v4
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