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Research on deep correlation filter tracking based on channel importance

Guosheng Yang, Chunting Li, Honglin Chen
2022 EURASIP Journal on Advances in Signal Processing  
The deep features extracted by the deep convolutional neural network have strong representation ability, so the tracking method based on the combination of correlation filter and deep convolutional neural  ...  However, the deep convolutional neural network largely restricts the real-time performance of the deep correlation filter tracking because of its complex network structure and heavy computation burden.  ...  algorithms, and various target tracking algorithms based on deep convolutional neural networks have been developed, such as deep convolutional neural network + correlation filter (DCNN + CF), deep convolutional  ... 
doi:10.1186/s13634-022-00860-9 fatcat:n26hxuzimrffhe6diuzyxdymbi

Visual Tracking via Deep Feature Fusion and Correlation Filters

Haoran Xia, Yuanping Zhang, Ming Yang, and Yufang Zhao
2020 Sensors  
of Convolutional Neural Networks are used to make the multi-layer features fusion improve the tracker learning accuracy.  ...  This paper builds a hybrid tracker combining the deep feature method and correlation filter to solve this challenge, and verifies its powerful characteristics.  ...  For the purpose of making visual tracking more robust, we proposes a correlation filtering object tracking algorithm that integrates with the HOG feature and the CNN layered feature.  ... 
doi:10.3390/s20123370 pmid:32545916 pmcid:PMC7349342 fatcat:wzt4qnuxjbgtflwdgkn5ki4md4

Multi-Stage Target Tracking with Drift Correction and Position Prediction

Xin Chen, Keyan Ren, Yibin Hou
2018 Journal of Physics, Conference Series  
We conduct tracking based on correlation filter with a corrective measure module to increase both performance and accuracy.  ...  Specifically, a convolutional network is used for solving the blur problem in realistic scene, training methodology that training dataset with blur images generated by the three blur algorithms.  ...  Acknowledgments This work was supported by The Aeronautical Science Foundations of China (No.20161375002) through a grants for our project.  ... 
doi:10.1088/1742-6596/1004/1/012010 fatcat:3ej5rsvojncbhj2uhwlt6wa3ue

Improved Hierarchical Convolutional Features for Robust Visual Object Tracking

Jinping Sun, Heng Liu
2021 Complexity  
Thus, to improve the tracking performance and robustness, an improved hierarchical convolutional features model is proposed into a correlation filter framework for visual object tracking.  ...  The filter model is updated only when these two maximum responses meet the threshold condition.  ...  from the convolution neural network to locate the target accurately. e deeper the convolution neural network is, the more obvious the background suppression is. e visualization results of the five convolution  ... 
doi:10.1155/2021/6690237 fatcat:h4dfgqxq6netlh2gsycpxxc3rm

Trajectory Smoothing Constraint and Hard Negative Mining for Distractor-aware Regression Tracking

Weichun Liu, Xiaoan Tang, Xiaoyuan Ren
2019 IEEE Access  
Recently, convolutional regression networks have drawn great attention in the tracking community.  ...  Convolutional regression trackers formulate the regression network as one convolutional layer and take advantages of end-to-end learning.  ...  Following this trend, convolutional regression trackers incorporate feature extraction and correlation filter learning into a unified convolutional neural network.  ... 
doi:10.1109/access.2019.2921562 fatcat:vk6u74aunrc3zahc7nhwdwg5oe

Robust Outdoor Vehicle Visual Tracking Based on k-Sparse Stacked Denoising Auto-Encoder [chapter]

Jing Xin, Xing Du, Yaqian Shi, Jian Zhang, Ding Liu
2018 Autonomous Vehicles [Working Title]  
Finally, confidence of each particle is computed by the classification neural network and is used for online tracking under particle filter framework.  ...  Robust visual tracking for outdoor vehicle is still a challenging problem due to large object appearance variations caused by illumination variation, occlusion, and fast motion.  ...  [18] combined convolutional neural networks with spatial-temporal saliency-guided sampling for object tracking in a correlated filter framework.  ... 
doi:10.5772/intechopen.80089 fatcat:oskoxmu3qnbtldeavke2hu3joa

Wide-Area Search Tracking for Siamese Region Proposal Network

Hongwei Zhang, Xiaoxia Li, Bin Zhu, Qi Ma
2020 IEEE Access  
We express our thanks for the experiment equipment provided by the lab.  ...  machine (SVM), convolutional neural network (CNN), and among others.  ...  [7] present a type of tracking algorithm based on a full convolutional neural network which results in more accuracy rate. Ma et al.  ... 
doi:10.1109/access.2020.3003347 fatcat:kuzvzwxb2fgipgusn64hyerskm

An adaptive eco with weighted feature for visual tracking

Yan Zhou, Hongwei Guo, Dongli Wang, Chunjiang Liao
2020 Filomat  
The efficient convolution operator (ECO) have manifested predominant results in visual object tracking.  ...  When adopting our ideas to adjust our tracker, the self-adaptive mechanism can avoid unnecessary training iterations, and the fuzzy update strategy reduces one fifth tracking computation compared to the  ...  In visual object tracking, there are two main-streams, the deep learning and discriminative correlation filter (DCF).  ... 
doi:10.2298/fil2015139z fatcat:5k32knjfkratbfg5l343iy7ude

VisDrone-SOT2018: The Vision Meets Drone Single-Object Tracking Challenge Results [chapter]

Longyin Wen, Pengfei Zhu, Dawei Du, Xiao Bian, Haibin Ling, Qinghua Hu, Chenfeng Liu, Hao Cheng, Xiaoyu Liu, Wenya Ma, Qinqin Nie, Haotian Wu (+61 others)
2019 Lecture Notes in Computer Science  
Single-object tracking, also known as visual tracking, on the drone platform attracts much attention recently with various applications in computer vision, such as filming and surveillance.  ...  To address this issue, the Vision Meets Drone Single-Object Tracking (VisDrone-SOT2018) Challenge workshop was organized in conjunction with the 15th European Conference on Computer Vision (ECCV 2018)  ...  A.7 Jointly weighted correlation filter and convolutional neural network (CFCNN) Wei Tian and Martin Lauer {wei.tian, martin.lauer}@kit.edu CFCNN combines both the correlation filter and the convolutional  ... 
doi:10.1007/978-3-030-11021-5_28 fatcat:qlmnwxvyurhgjdjfleisfi3jxu

Target-Aware Deep Feature Compression for Power Intelligent Inspection Tracking

Wei Jiang, Zhimin Guo, Huanlong Zhang, Liyun Cheng, Yangyang Tian, Yang Li
2022 Journal of Electrical and Computer Engineering  
This paper presents a target-aware deep feature compression for power intelligent inspection tracking.  ...  Based on this, the deep feature compression model is combined with Siamese tracking framework to achieve real-time and robust tracking.  ...  scale estimation for robust visual tracking (DSST) [38] , method high-speed tracking with kernelized correlation filters (KCF) [39] , the deep featurebased methods include method hierarchical convolutional  ... 
doi:10.1155/2022/3161551 fatcat:qvx6bdj3qjdi7oqepvbazg5gli

Object-Aware Adaptive Convolution Kernel Attention Mechanism in Siamese Network for Visual Tracking

Dongliang Yuan, Qingdang Li, Xiaohui Yang, Mingyue Zhang, Zhen Sun
2022 Applied Sciences  
As a classic framework for visual object tracking, the Siamese convolutional neural network has received widespread attention from the research community.  ...  In this work, we observe that the contribution of each convolution kernel in the convolutional neural network for object tracking tasks is different.  ...  The visual tracking techniques are based on correlation filter-based methods, deep learning-based methods, and transformer-based methods.  ... 
doi:10.3390/app12020716 doaj:d2662afe72c047ef980fe7ea86e84b83 fatcat:zcvsvnff5faf5grkbltf5tagu4

Research and Implementation of Robot Vision Scanning Tracking Algorithm Based on Deep Learning

Haifeng Guo, Wenyi Li, Na Zhou, He Sun, Zhao Han, Danilo Pelusi
2022 Scanning  
In order to solve the difficult problem of deep learning-based robot vision tracking algorithm research and implementation, a deep learning-based target tracking algorithm and a classical tracking algorithm  ...  The results show that the performance of the TLD algorithm is poor regardless of the accuracy curve or the accuracy curve, and the performance of GOTURN-LD is significantly improved when the illumination  ...  to the birth of convolutional neural network.  ... 
doi:10.1155/2022/3330427 pmid:35950087 pmcid:PMC9345732 fatcat:5hcje4iqtzagdjdlzqzu3twrkq

Visual tracking based on transfer learning of deep salience information

Zuo Haorui, Xu Zhiyong, Zhang Jianlin, Jia Ge
2020 Opto-Electronic Advances  
Complicated representations of image features can be gained by the function of every layer in convolution neural network (CNN).  ...  The characteristic of biology vision in attention-based salience is similar to the neuroscience features of convolution neural network.  ...  We express our thanks for the experiment equipment provided by the lab. We appreciate the support of the relevant department.  ... 
doi:10.29026/oea.2020.190018 doaj:e230fac26e2948d28ca973523f087436 fatcat:skxrt4q2yrdeheanqjpwfyjnau

Real-Time Multitarget Tracking for Panoramic Video Based on Dual Neural Networks for Multisensor Information Fusion

Qing Lin, Zhihan Lv
2022 Mathematical Problems in Engineering  
A multitarget real-time tracking system for panoramic video with multisensor information fusion dual neural networks is studied and implemented by combining dual neural networks, fused geometric features  ...  The proposed panoramic video multitarget real-time tracking algorithm based on the dual neural network can effectively improve the target tracking accuracy of the model on degraded frames (motion blur,  ...  And with the development of deep learning, researchers have proposed end-to-end multitarget tracking networks that use convolutional neural networks or recurrent neural networks for target tracking. e  ... 
doi:10.1155/2022/8313471 fatcat:soiwm5sbovawxfrxuvs47ydyoy

A SMALL TARGET VISUAL TRACKING METHOD FOR UNMANNED AERIAL VEHICLE PLATFORM UNDER CONVOLUTIONAL NEURAL NETWORK

2020 International Journal of Mechatronics and Applied Mechanics  
In order to explore the easy loss of tracking target in the realization of Unmanned Aerial Vehicle (UAV) platform visual target tracking, the convolutional neural network algorithm is proposed to improve  ...  Therefore, the lightweight convolutional neural network algorithm proposed in this research lays the application foundation for target detection of UAV platform and further promotes the development of  ...  Figure 1 : 1 Target detection model of Mobile Net V2 based on convolutional neural network A Small Target Visual Tracking Method for Unmanned Aerial Vehicle Platform under Convolutional Neural Network  ... 
doi:10.17683/ijomam/issue8.7 fatcat:6d73roge6rcwpk2dls5jieexda
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