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Multiple Cues-Based Robust Visual Object Tracking Method

Baber Khan, Abdul Jalil, Ahmad Ali, Khaled Alkhaledi, Khizer Mehmood, Khalid Mehmood Cheema, Maria Murad, Hanan Tariq, Ahmed M. El-Sherbeeny
2022 Electronics  
Kernelized correlation filter- (KCF) based tracking schemes have shown good performance in recent years.  ...  We update the following tracking modules based on hybridized criterion: (i) occlusion detection, (ii) adaptive learning rate adjustment, (iii) drift handling using adaptive learning rate, (iv) handling  ...  In [18] , the author proposed adaptive multi-scale correlation filter-based tracking to address the scale variation problem, which exists in the original KCF scheme.  ... 
doi:10.3390/electronics11030345 fatcat:setvps6ah5fdznryefselbzemu

AFAM-PEC: Adaptive Failure Avoidance Tracking Mechanism using Prediction-Estimation Collaboration

Baber Khan, Ahmad Ali, Abdul Jalil, Khizer Mehmood, Maria Murad, Hamdan Awan
2020 IEEE Access  
Currently, adaptive correlation filter based tracking algorithms are being combined with redetection modules. This hybridization helps in redetection of the target in long term tracking.  ...  During recent years correlation tracking is considered fast and effective by the virtue of circulant structure of the sampling data for learning phase of filter and Fourier domain calculation of correlation  ...  The second limitation of correlation filter based tracking is solved in [3] by learning multiple correlation filters having different learning rates.  ... 
doi:10.1109/access.2020.3015580 fatcat:4xspq3oerzhxrfokxfhaampday

Beyond Background-Aware Correlation Filters: Adaptive Context Modeling by Hand-Crafted and Deep RGB Features for Visual Tracking [article]

Seyed Mojtaba Marvasti-Zadeh, Hossein Ghanei-Yakhdan, Shohreh Kasaei
2021 arXiv   pre-print
On the other hand, the recent deep learning-based visual tracking methods have provided a competitive performance along with extensive computations.  ...  In recent years, the background-aware correlation filters have achie-ved a lot of research interest in the visual target tracking.  ...  Compliance with Ethical Standards: All authors declare that they have no conflict of interest.  ... 
arXiv:2004.02932v2 fatcat:dbjgzsequvcpxgq2qlilv6rmbi

VCIP 2020 Index

2020 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)  
Gao, Wen Point Cloud Geometry Prediction Across Spati Scale using Deep Learning Gao, Yanbo A Mixed Appearance-based and Coding Distortionbased CNN Fusion Approach for In- loop Filtering in Video  ...  Images Ozcinar, Cagri Towards Audio-Visual Saliency Prediction for Omnidirectional Video with Spatial Audio T P Palomino, Daniel Power/QoS-Adaptive HEVC FME Hardware using Machine Learning-Based  ... 
doi:10.1109/vcip49819.2020.9301896 fatcat:bdh7cuvstzgrbaztnahjdp5s5y

A Hybrid Visual Tracking Algorithm Based on SOM Network and Correlation Filter

Yuanping Zhang, Xiumei Huang, Ming Yang
2021 Sensors  
A reliable method of robust target tracking is proposed, based on multiple adaptive correlation filters with a memory function of target appearance at the same time.  ...  To meet the challenge of video target tracking, based on a self-organization mapping network (SOM) and correlation filter, a long-term visual tracking algorithm is proposed.  ...  Compared with the tracking algorithm based on the online learning sparse sample classifier [48] [49] [50] (random sampling surround the estimated target position), our method is based on the correlation  ... 
doi:10.3390/s21082864 pmid:33921720 fatcat:wjjka6tnojgytohpwms7xhtuda

Superpixel Tensor Pooling for Visual Tracking using Multiple Midlevel Visual Cues Fusion

Chong Wu, Le Zhang, Jiawang Cao, Hong Yan
2019 IEEE Access  
To validate the proposed method, we compare it with state-of-the-art methods on 24 sequences with multiple visual tracking challenges.  ...  Then the incremental positive and negative subspaces learning is performed.  ...  Cyan box: Ours; Yellow box: robust superpixels tracking (SPT); Red box: discriminative tracking using tensor pooling (TPT); Green box: correlation-filter based scale-adaptive visual tracking with hybrid-scheme  ... 
doi:10.1109/access.2019.2946939 fatcat:iv5mxdk26bgqzkuc6scrjr3zmy

Learning Compact Target-Oriented Feature Representations for Visual Tracking [article]

Chenglong Li, Yan Huang, Liang Wang, Jin Tang, Liang Lin
2019 arXiv   pre-print
correlation filter framework.  ...  The feature representations and the correlation filter are jointly learnt to enhance to each other via a fast solver which only has very slight computational burden on the tracking speed.  ...  It is because our tracker uses a simple strategy that samples a sparsely set of scaled regions from an image pyramid and then evaluates them using a HOG-based correlation filter for scale estimation.  ... 
arXiv:1908.01442v1 fatcat:335wl2epdjggtc7iee2fqqtjpq

A Robust Object Tracking Method for Surveillance Applications to Handle Occlusion

Madah-Ul- Mustafa, School of Automation Science and Engineering, South China University of Technology, Guangzhou 510641, China, Zhu Liang Yu
2021 Journal of clean energy technologies  
The proposed scheme adopts an efficient integration of motion modeling via particle-kalman-filter (PKF) into the kernelized correlation filter (KCF) tracking framework to achieve an efficient and robust  ...  Secondly we proposed a robust tracking scheme that can handle occlusion and drift problems as well as other visual object tracking challenges to predict the target object position when occlusion is occurred  ...  Furthermore, hybrid methods i.e. combination of proposed method with deep learning based methods is worth exploring and may provide more room for further improvement in feature learning and visual understanding  ... 
doi:10.7763/ijcte.2021.v13.1283 fatcat:wvxodbdbinhbzgvvb2fp5hlmuy

Robust Scale Adaptive and Real-Time Visual Tracking with Correlation Filters

Jiatian PI, Keli HU, Yuzhang GU, Lei QU, Fengrong LI, Xiaolin ZHANG, Yunlong ZHAN
2016 IEICE transactions on information and systems  
We apply the discriminative correlation filter for scale estimation as an independent part after finding the optimal translation based on the KCF tracker.  ...  This paper presents an appealing tracker with robust scale estimation, which can handle the problem of fixed template size in Kernelized Correlation Filter (KCF) tracker with no significant decrease in  ...  With more correlation filter-based trackers [18] - [21] developed recently, correlation filter-based tracking model has proven its great strengths in efficiency and robustness, and has considerably  ... 
doi:10.1587/transinf.2015edp7459 fatcat:mpamehthdjgrpkwmaxexaxvldu

2020 Index IEEE Transactions on Cybernetics Vol. 50

2020 IEEE Transactions on Cybernetics  
Yao, T., +, TCYB Dec. 2020 4896-4907 Learning Scale-Adaptive Tight Correlation Filter for Object Tracking.  ...  ., +, TCYB March 2020 1321-1332 Learning Scale-Adaptive Tight Correlation Filter for Object Tracking. Zhang, S., +, TCYB Jan. 2020 270-283 Text Image Deblurring Using Kernel Sparsity Prior.  ... 
doi:10.1109/tcyb.2020.3047216 fatcat:5giw32c2u5h23fu4drupnh644a

Sequential Monte Carlo-guided ensemble tracking

Yuru Wang, Qiaoyuan Liu, Longkui Jiang, Minghao Yin, Shengsheng Wang, Quan Zou
2017 PLoS ONE  
the sample scales.  ...  Moreover, to increase the tracking accuracy, weak classifiers including Support Vector Machine (SVM) and Large Margin Distribution Machine (LDM) are combined as a hybrid strong one, with adaptiveness to  ...  To obtain more robustness and generality, this paper generalized LDM to the tracking problem and constructed a hybrid classifier adapted with feature scales.  ... 
doi:10.1371/journal.pone.0173297 pmid:28399149 pmcid:PMC5388463 fatcat:y4zlf52glre2tjfyhmsav7ey7y

A Bayesian Approach to Tracking Learning Detection [chapter]

Giorgio Gemignani, Wongun Choi, Alessio Ferone, Alfredo Petrosino, Silvio Savarese
2013 Lecture Notes in Computer Science  
We describe a novel framework based on Tracking-Learning-Detection (TLD), that combine bayesian optimal filtering with pn on-line learning theory [12] to adapt target visual likelihood during tracking.  ...  Tracking objects of interest in video sequences, referred in computer vision literature as video tracking or visual tracking, is an essential task for intelligent machines able to understand and react  ...  We propose to employ a sampling based sequential filtering technique based on the MCMC particle filter.  ... 
doi:10.1007/978-3-642-41181-6_81 fatcat:zqrtwmr3i5hijge75e7o7gcq5e

Long-term Correlation Tracking using Multi-layer Hybrid Features in Sparse and Dense Environments [article]

Nathanael L. Baisa, Deepayan Bhowmik, Andrew Wallace
2019 arXiv   pre-print
In this paper, we propose a new long-term visual tracking algorithm, learning discriminative correlation filters and using an online classifier, to track a target of interest in both sparse and crowded  ...  First, we learn a translation correlation filter using a multi-layer hybrid of convolutional neural networks (CNN) and traditional hand-crafted features.  ...  Index Terms-Visual tracking, Correlation filter, CNN features, Hybrid features, Online learning, GM-PHD filter I.  ... 
arXiv:1705.11175v6 fatcat:4poqd3nklzbthbo5dwfkucoplm

Long-term correlation tracking using multi-layer hybrid features in sparse and dense environments

Nathanael L. Baisa, Deepayan Bhowmik, Andrew Wallace
2018 Journal of Visual Communication and Image Representation  
In this paper, we propose a new long-term visual tracking algorithm, learning discriminative correlation filters and using an online classifier, to track a target of interest in both sparse and crowded  ...  First, we learn a translation correlation filter using a multi-layer hybrid of convolutional neural networks (CNN) and traditional hand-crafted features.  ...  though both methods use similar visual features (HOG) to learn the scale correlation filter.  ... 
doi:10.1016/j.jvcir.2018.06.027 fatcat:4p7rfnfslzdtlpccp3q722dui4

Table of Contents

2022 IEEE Transactions on Cybernetics  
Event-Triggered Stabilization of a Linear System With Model Uncertainty and i.i.d. Feedback Dropouts . .  ...  Pang 1086 Cooperative Adaptive Iterative Learning Fault-Tolerant Control Scheme for Multiple Subway Trains . . . . . . . . .G. Liu and Z.  ...  Joo 1312 H ∞ Scaled Consensus for MASs With Mixed Time Delays and Disturbances via Observer-Based Output Feedback . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/tcyb.2022.3149188 fatcat:7ymp44ixhjgwhnfgdcx7ggm4h4
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