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Deep Motion-Appearance Convolutions for Robust Visual Tracking

Haojie Li, Sihang Wu, Shuangping Huang, Kin-Man Lam, Xiaofen Xing
2019 IEEE Access  
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  ...  INDEX TERMS Visual tracking, 3D convolutional kernels, motion-appearance. SIHANG WU received the B.S. degree from  ...  To the best of our knowledge, this is the first work to introduce a deep 3D convolutional network for object tracking. 3) We propose an Inverse Temporal Training (ITT) strategy, for introducing deep motion  ... 
doi:10.1109/access.2019.2958405 fatcat:777v6zmdobgk5njbvsxsuv5x4i

Deep Motion Features for Visual Tracking [article]

Susanna Gladh, Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg
2016 arXiv   pre-print
To the best of our knowledge, we are the first to propose fusing appearance information with deep motion features for visual tracking.  ...  Contrary to visual tracking, deep motion features have been successfully applied for action recognition and video classification tasks.  ...  In this work, we propose to combine appearance cues with deep motion information for visual tracking. III.  ... 
arXiv:1612.06615v1 fatcat:jahqeo3i4rdppcfgfhdsu7hmli

A Narrow Deep Learning Assisted Visual Tracking with Joint Features

Xiaoyan Qian, Daihao Zhang
2020 Mathematical Problems in Engineering  
to give the robust representation for visual tracking.  ...  A robust tracking method is proposed for complex visual sequences.  ...  Many thanks are due to the original authors for providing the TB-100 dataset that is publicly available online at http://cvlab.hanyang.ac.kr/ tracker benchmark/datasets.html.  ... 
doi:10.1155/2020/8659890 fatcat:6e5egqqwhjdr7ogfkrc7bdrkui

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  
Constructing a robust appearance model of the visual object is a crucial task for visual object tracking.  ...  Finally, our spatiotemporal fusion feature from STResNet appearance model is incorporated into the correlation filter for robust visual object tracking.  ...  This deep spatiotemporal appearance model is jointly trained offline end-to-end to achieve improved accuracy and robustness in visual object tracking.  ... 
doi:10.1109/access.2019.2903161 fatcat:uas76gauobcspkjwvuvy6wpevi

Robust Visual Object Tracking with Two-Stream Residual Convolutional Networks [article]

Ning Zhang, Jingen Liu, Ke Wang, Dan Zeng, Tao Mei
2020 arXiv   pre-print
tracking, which successfully exploits both appearance and motion features for model update.  ...  Inspired by the human "visual tracking" capability which leverages motion cues to distinguish the target from the background, we propose a Two-Stream Residual Convolutional Network (TS-RCN) for visual  ...  Although motion is an important cue for video understanding, there are only a few attempts to exploit motion cues for visual object tracking in most recent deep learning based tracking approaches.  ... 
arXiv:2005.06536v1 fatcat:5mhnd5pb7zgupp4mzd72mjf5sm

Deep motion features for visual tracking

Susanna Gladh, Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg
2016 2016 23rd International Conference on Pattern Recognition (ICPR)  
In this work, we propose to combine appearance cues with deep motion information for visual tracking. III.  ...  This motivates us to investigate the fusion of standard appearance features with deep motion features for visual tracking.  ... 
doi:10.1109/icpr.2016.7899807 dblp:conf/icpr/GladhDKF16 fatcat:i5t6cggl3bevhlaokvwrbg2d6u

Deep Learning Trackers Review and Challenge

Yongxiang Gu, Beijing Chen, Xu Cheng, Yifeng Zhang, Jingang Shi
2019 Journal of Information Hiding and Privacy Protection  
H. (2015): Hierarchical convolutional features for visual tracking. Baek, M.; Han, B. (2016): Modeling and propagating cnns in a tree structure for visual tracking. arXiv:1608.07242.  ...  .; Yang, M. (2016): Visual tracking via coarse and fine structural local sparse appearance models.  ...  Network function For visual tracking, deep networks can be not only used for extracting effective features but also adopted for evaluating the candidates of the tracked object.  ... 
doi:10.32604/jihpp.2019.05938 fatcat:z2kq47sl25fz7fykzdhfozysge

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  
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.  ...  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.  ...  Described a motion net (MotionNet) to fulfill end-to-end trainable motion detection and an appearance net (AppearanceNet) for multi-scale appearance matchingto achieve object localization. [Q.  ... 
doi:10.17577/ijertv9is010309 fatcat:e7wny2gl35cuvfxrcfec3zxn7y

Object Tracking in Satellite Videos Based on Convolutional Regression Network with Appearance and Motion Features

Zhaopeng Hu, Daiqin Yang, Kao Zhang, Zhenzhong Chen
2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
Instead of handcrafted features, both appearance features and motion features, which are extracted by pretrained deep neural networks, are used for accurate object tracking.  ...  Index Terms-Convolutional neural networks (CNNs), deep learning, object tracking, satellite video.  ...  By combining deep appearance and motion features, the complementary information can provide robust tracking.  ... 
doi:10.1109/jstars.2020.2971657 fatcat:ug4xfrsl4vfgvgsamcnjtnrzqe

A Robust Visual Tracking Algorithm Based on Spatial-Temporal Context Hierarchical Response Fusion

Wancheng Zhang, Yanmin Luo, Zhi Chen, Yongzhao Du, Daxin Zhu, Peizhong Liu
2018 Algorithms  
Furthermore, we proposed a re-detection activation discrimination method to improve the robustness of visual tracking in the case of tracking failure and an adaptive model update method to reduce tracking  ...  Discriminative correlation filters (DCFs) have been shown to perform superiorly in visual object tracking.  ...  Hierarchical Feature of Convolution Layer The hierarchical features of deep neural networks play an important role in visual object tracking, which can enhance the robustness and accuracy of visual tracking  ... 
doi:10.3390/a12010008 fatcat:htv33er4hjgzlnv6n3v4m7amrm

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]  
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.  ...  vehicle tracking method under particle filter inference is further proposed to solve the problem of appearance variance during the tracking.  ...  appearance in visual tracking.  ... 
doi:10.5772/intechopen.80089 fatcat:oskoxmu3qnbtldeavke2hu3joa

Adaptive hyper-feature fusion for visual tracking (February 2020)

Zhi Chen, Yongzhao Du, Jianhua Deng, Jiafu Zhuang, Peizhong Liu
2020 IEEE Access  
In this work, we propose a robust tracking algorithm based on context-aware correlation filter framework.  ...  convolutional features (such as VGGNet).  ...  The HCFTstar [8] effectively combines multiple layers of deep hierarchical convolutional features for visual tracking.  ... 
doi:10.1109/access.2020.2986157 fatcat:bvzg55ebnjekdj6y3cfbzz3hya

Effective Fusion of Deep Multitasking Representations for Robust Visual Tracking [article]

Seyed Mojtaba Marvasti-Zadeh, Hossein Ghanei-Yakhdan, Shohreh Kasaei, Kamal Nasrollahi, Thomas B. Moeslund
2021 arXiv   pre-print
terms of precision and robustness of visual tracking.  ...  This paper aims to evaluate the performance of twelve state-of-the-art ResNet-based FENs in a DCF-based framework to determine the best for visual tracking purposes.  ...  [26] have investigated the fusion of handcrafted appearance features (e.g., HOG and CN) with deep RGB and motion features in the DCF-based visual tracking framework.  ... 
arXiv:2004.01382v2 fatcat:hsns3y46g5c7vdghlmgbzlniji

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.  ...  We take both convolutional features and handcrafted features into account to robustly encode the target appearance.  ...  It is updated incrementally to accommodate appearance changes over time for robust visual tracking.  ... 
doi:10.1007/s41095-017-0087-3 fatcat:4miqlot67vhpfc2idgyag4ka5a

Classifier Adaptive Fusion: Deep Learning for Robust Outdoor Vehicle Visual Tracking

Jing Xin, Xing Du, Yaqian Shi
2019 IEEE Access  
However, single deep auto-encoder model would not be robust enough to represent the appearance model of outdoor vehicle for its harsh working environment, such as illumination variation, occlusion, cluttered  ...  In this paper, a novel multiple-DAE-based tracking approach, that is, classifier adaptive fusion for robust outdoor vehicle visual tracking approach is proposed under particle filter framework.  ...  [27] trained convolutional neural networks through online video images rather than offline images to learn complex motion features for object tracking.  ... 
doi:10.1109/access.2019.2936433 fatcat:5iybole2brdc3dw2g7azv5ysby
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