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Jointly Feature Learning and Selection for Robust Tracking via a Gating Mechanism

Bineng Zhong, Jun Zhang, Pengfei Wang, Jixiang Du, Duansheng Chen, Quan Zou
2016 PLoS ONE  
To achieve effective visual tracking, a robust feature representation composed of two separate components (i.e., feature learning and selection) for an object is one of the key issues.  ...  In online tracking, the pre-trained CPGDN model is fine-tuned to adapt to the tracking specific objects.  ...  To effectively transfer pre-trained deep features for online tracking, Wang et al. [28] present a sequential training method for convolutional neural networks.  ... 
doi:10.1371/journal.pone.0161808 pmid:27575684 pmcid:PMC5004979 fatcat:oizomflejrbt5ajei5aej4kbpe

A Robust Visual Tracking Method through Deep Learning Features

Jia-zhen XU, Ming-zhang ZUO, Lin YANG, Lei HUANG
2017 DEStech Transactions on Computer Science and Engineering  
In this paper, we propose a novel approach based on correlation filter framework for robust scale estimation through deep learning features.  ...  Object tracking is one of the most important components in many applications of computer vision.  ...  The first trial is the proposal of Minimum Output Sum of Squared Error (MOSSE) [4] filter. Using an adaptive training scheme, MOSSE is considerably robust and efficient in tracking.  ... 
doi:10.12783/dtcse/aita2016/7562 fatcat:xhhecaysvngyzitndm27u4lfei

Fully Convolutional Online Tracking [article]

Yutao Cui, Cheng Jiang, Limin Wang, Gangshan Wu
2021 arXiv   pre-print
Our key contribution is to introduce an online regression model generator (RMG) for initializing weights of the target filter with online samples and then optimizing this target filter weights based on  ...  Online learning has turned out to be effective for improving tracking performance.  ...  This simple tracking recipe not only allows for efficient training and deployment, but also enables online learning on both branches for accurate and robust tracking. • We design a Regression Model Generator  ... 
arXiv:2004.07109v5 fatcat:lxwkgvz73vejrnjbgn6ydus4cu

Instrument Tracking via Online Learning in Retinal Microsurgery [chapter]

Yeqing Li, Chen Chen, Xiaolei Huang, Junzhou Huang
2014 Lecture Notes in Computer Science  
Robust visual tracking of instruments is an important task in retinal microsurgery.  ...  To address these problems, we propose a new approach for robust instrument tracking.  ...  It is adaptively trained and updated on the fly. Samples for online updating are collected by a filtering process, which selects "unfamiliar" positive samples and "hard" negative samples.  ... 
doi:10.1007/978-3-319-10404-1_58 fatcat:hicbney7ljarxf2plhkb7ue4lq

Robust Visual Object Tracking with Top-down Reasoning

Mengdan Zhang, Jiashi Feng, Weiming Hu
2017 Proceedings of the 2017 ACM on Multimedia Conference - MM '17  
In generic visual tracking, traditional appearance based trackers suffer from distracting factors like bad lighting or major target deformation, etc., as well as insufficiency of training data.  ...  In this work, we propose to exploit the category-specific semantics to boost visual object tracking, and develop a new visual tracking model that augments the appearance based tracker with a top-down reasoning  ...  These CNNs may degrade in the online tracking process for lack or poor quality of the training samples, which leads to over-fitting and tracking error accumulation.  ... 
doi:10.1145/3123266.3123449 dblp:conf/mm/ZhangFH17 fatcat:77j2apo4gfadblemtv65rssfl4

A Scale-Adaptive Particle Filter Tracking Algorithm Based on Offline Trained Multi-Domain Deep Network

Yiming Tang, Yufei Liu, Hong Huang, Jiamin Liu, Wenjie Xie
2020 IEEE Access  
After training, the shared convolutional units are remained as an observation model for our tracking framework.  ...  INDEX TERMS Visual tracking, convolutional neural network (CNN), multi-domain learning, particle filter, scale-adaptive.  ...  CONCLUSION To build a robust online tracking framework for visual tracking tasks, this paper presents a novel tracking method based on deep network and particle filter.  ... 
doi:10.1109/access.2020.2973338 fatcat:uqz67quz65finoaioieegyakbe

Visual Target Tracking using Robust Information Interaction between Single Tracker and Online Model

Yeyi Gu, Xinmin Zhou, Minjie Wan, Guohua Gu, Yansong Wang
2018 MATEC Web of Conferences  
In this paper, a novel tracking algorithm based on the cooperative operation of online appearance model and typical tracking in contiguous frames is proposed.  ...  First of all, to achieve satisfactory performances in challenging scenes, we focus on establishing a robust discriminative tracking model with linear Support Vector Machine (SVM) and use the particle filter  ...  In recent years, the framework of tracking-bydetection [1] [2] [3] has become the mainstream scheme for visual object tracking, where the key is to find the candidate sample that most closely matches  ... 
doi:10.1051/matecconf/201823202046 fatcat:tpjldg4mf5bsxgcosyaqfbw54a

Object tracking using a convolutional network and a structured output SVM

Junwei Li, Xiaolong Zhou, Sixian Chan, Shengyong Chen
2017 Computational Visual Media  
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.  ...  Secondly, we employ a structured output SVM for refining the target's location to mitigate uncertainty in labeling samples as positive or negative.  ...  Numerous auxiliary data are required for offline training the deep networks; the pre-trained model is then used for online visual tracking.  ... 
doi:10.1007/s41095-017-0087-3 fatcat:4miqlot67vhpfc2idgyag4ka5a

Generic Multiview Visual Tracking [article]

Minye Wu, Haibin Ling, Ning Bi, Shenghua Gao, Hao Sheng, Jingyi Yu
2019 arXiv   pre-print
The two components are integrated into a correlation filter tracking framework, where the features are trained offline using existing single view tracking datasets.  ...  Moreover, during tracking, we assemble information across different cameras to dynamically update a novel collaborative correlation filter (CCF), which is shared among cameras to achieve robustness against  ...  These strategies, as demonstrated in our carefully designed experiments, clearly improve the tracking robustness. Multiview Visual Tracking Multi-camera inputs have been used for visual tracking.  ... 
arXiv:1904.02553v1 fatcat:spyugbcu65dnhd4ivyqsngnhgy

Learning Multi-domain Convolutional Neural Networks for Visual Tracking

Hyeonseob Nam, Bohyung Han
2016 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
Online tracking is performed by evaluating the candidate windows randomly sampled around the previous target state.  ...  We propose a novel visual tracking algorithm based on the representations from a discriminatively trained Convolutional Neural Network (CNN).  ...  Finally, a smaller network is obviously more efficient in visual tracking problem, where training and testing are performed online.  ... 
doi:10.1109/cvpr.2016.465 dblp:conf/cvpr/NamH16 fatcat:dlpb5rrtz5agrcpyspqqiziyre

Learning Multi-Domain Convolutional Neural Networks for Visual Tracking [article]

Hyeonseob Nam, Bohyung Han
2016 arXiv   pre-print
Online tracking is performed by evaluating the candidate windows randomly sampled around the previous target state.  ...  We propose a novel visual tracking algorithm based on the representations from a discriminatively trained Convolutional Neural Network (CNN).  ...  Finally, a smaller network is obviously more efficient in visual tracking problem, where training and testing are performed online.  ... 
arXiv:1510.07945v2 fatcat:gbojryn4oret5khblhvysqlg7m

An Analytical Review on Some Recent Advances in Deep Learning Object Tracking Approaches

K. Nani Kumar, M. James Stephen, P. V. G. D. Prasad Reddy, Andhra University
2020 International Journal of Engineering Research and  
Visual Object tracking in real world, real time application scenarios is a complex problem, therefore, it remains a most active area of research in computer vision.  ...  This paper presents a detailed review on some of the recent advances in Deep Learning Based Visual Object Tracking Approaches from a wide variety of algorithms often cited in research literature.  ...  of the model. • Integration of both offline and online training methods may lead to more robust visual trackers. • Improving tracking efficiency in handling simultaneously challenging visual attributes  ... 
doi:10.17577/ijertv9is010309 fatcat:e7wny2gl35cuvfxrcfec3zxn7y

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.  ...  [4] proposed adaptive multiple cues integration for robust outdoor vehicle visual tracking in the particle filter framework.  ... 
doi:10.5772/intechopen.80089 fatcat:oskoxmu3qnbtldeavke2hu3joa

The Research and Application of Visual Saliency and Adaptive Support Vector Machine in Target Tracking Field

Yuantao Chen, Weihong Xu, Fangjun Kuang, Shangbing Gao
2013 Computational and Mathematical Methods in Medicine  
They are very difficult to estimate the target states, illumination change, target shape changes, complex backgrounds, and other factors and all affect the occlusion in tracking robustness.  ...  To further improve the target tracking's accuracy and reliability, we present a novel target tracking algorithm to use visual saliency and adaptive support vector machine (ASVM).  ...  robust target tracking algorithm.  ... 
doi:10.1155/2013/925341 pmid:24363779 pmcid:PMC3865687 fatcat:u7wu7mup4nbvdmskr574kfau3q

Real-Time Visual Tracking with Variational Structure Attention Network

Yeongbin Kim, Joongchol Shin, Hasil Park, Joonki Paik
2019 Sensors  
Online training framework based on discriminative correlation filters for visual tracking has recently shown significant improvement in both accuracy and speed.  ...  Through the proposed structure–attention framework, discriminative correlation filters can learn robust structure information of targets during online training with an enhanced discriminating performance  ...  .; visualization, Y.K.; supervision, H.P. and J.P.; project administration, J.P.; funding acquisition, J.P. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s19224904 pmid:31717609 pmcid:PMC6891527 fatcat:hin7n2tajrbt7knst4uklduleq
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