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Learning Support Correlation Filters for Visual Tracking [article]

Wangmeng Zuo, Xiaohe Wu, Liang Lin, Lei Zhang, Ming-Hsuan Yang
2016 arXiv   pre-print
We incorporate the discrete Fourier transform with the proposed alternating optimization process, and pose the tracking problem as an iterative learning of support correlation filters (SCFs) which find  ...  Recently, the circulant matrix formed by dense sampling of translated image patches has been utilized in correlation filters for fast tracking.  ...  CONCLUSIONS We propose an effective and efficient approach to learn support correlation filters for real time visual tracking.  ... 
arXiv:1601.06032v1 fatcat:c6t37hdqhrfs5bzdqu3ue64dj4

Learning Support Correlation Filters for Visual Tracking

Wangmeng Zuo, Xiaohe Wu, Liang Lin, Lei Zhang, Ming-Hsuan Yang
2018 IEEE Transactions on Pattern Analysis and Machine Intelligence  
We incorporate the discrete Fourier transform with the proposed alternating optimization process, and pose the tracking problem as an iterative learning of support correlation filters (SCFs).  ...  For visual tracking methods based on kernel support vector machines (SVMs), data sampling is usually adopted to reduce the computational cost in training.  ...  CONCLUSIONS We propose an effective and efficient approach to learn support correlation filters for real time visual tracking.  ... 
doi:10.1109/tpami.2018.2829180 pmid:29993910 fatcat:2maehc56ifht7ihursslj54xn4

Real-time face tracking under long-term full occlusions

Martin Soldic, Darijan Marcetic, Marijo Maracic, Darko Mihalic, Slobodan Ribaric
2017 Proceedings of the 10th International Symposium on Image and Signal Processing and Analysis  
loss estimation based on a response of a position correlation filter, a candidate image patch selection for reinitialization supported with a short-and long-term memories (STM and LTM).  ...  position correlation filters (online learned) is used to recover the tracker from long-term full occlusions.  ...  ACKNOWLEDGMENTS This work has been supported by the Croatian Science Foundation under project 6733 De-identification for Privacy Protection in Surveillance Systems (DePPSS).  ... 
doi:10.1109/ispa.2017.8073586 dblp:conf/imspa/SoldicMMMR17 fatcat:kb6lz472vrgxdewrlhqyih6b34

Discriminative Fusion Correlation Learning for Visible and Infrared Tracking

Xiao Yun, Yanjing Sun, Xuanxuan Yang, Nannan Lu
2019 Mathematical Problems in Engineering  
Discriminative correlation filter- (DCF-) based trackers are computationally efficient and achieve excellent tracking in challenging applications.  ...  Therefore, this paper proposes a discriminative fusion correlation learning model to improve DCF-based tracking performance by efficiently combining multiple features from visible and infrared images.  ...  Acknowledgments This work is supported by the Natural Science Foundation of Jiangsu Province (BK20180640, BK20150204),  ... 
doi:10.1155/2019/2437521 fatcat:xqfjdd2p4nht3hdq66h23eihmm

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
In recent years, the background-aware correlation filters have achie-ved a lot of research interest in the visual target tracking.  ...  On the other hand, the recent deep learning-based visual tracking methods have provided a competitive performance along with extensive computations.  ...  Discriminative correlation filters (DCF) are the most popular branch of tracking-by-detection that learn the target model via learning correlation filters by a set of training samples.  ... 
arXiv:2004.02932v2 fatcat:dbjgzsequvcpxgq2qlilv6rmbi

Evaluation of Feature Channels for Correlation-Filter-Based Visual Object Tracking in Infrared Spectrum

Erhan Gundogdu, Aykut Koc, Berkan Solmaz, Riad I. Hammoud, A. Aydin Alatan
2016 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
Correlation filters for visual object tracking in visible imagery has been well-studied.  ...  The highest performance in terms of the overlap metric is achieved when these deep CNN features are utilized in a correlation-filter-based tracker.  ...  In [17] , an online structured-output support vector machine (SVM) is designed for visual tracking.  ... 
doi:10.1109/cvprw.2016.43 dblp:conf/cvpr/GundogduKSHA16 fatcat:q5zzxuvhh5b2hdai2f3h75sq4y

Learning target-aware correlation filters for visual tracking

Dongdong Li, Gongjian Wen, Yangliu Kuai, Jingjing Xiao, Fatih Porikli
2019 Journal of Visual Communication and Image Representation  
To tackle this problem, we propose Target-Aware Correlation Filters (TACF) for visual tracking.  ...  Discriminative Correlation Filters (DCF) have achieved enormous popularity in the tracking community.  ...  Acknowledgements This work is supported by the National Natural Science Foundation of China (NSFC) (No. 41601487, 61701506) .  ... 
doi:10.1016/j.jvcir.2018.11.036 fatcat:5bzqcwec45hz7nwmrnzyyh3xvy

Adaptive Learning Rate for Visual Tracking Using Correlation Filters

C.S. Asha, A.V. Narasimhadhan
2016 Procedia Computer Science  
Existing correlation filters use fixed learning rate to update filter template in every frame.  ...  This method uses integral channel features in correlation filter framework with adaptive learning rate to efficiently track the object.  ...  In this section, different types of channel features are discussed, which can be used with correlation filter for visual tracking.  ... 
doi:10.1016/j.procs.2016.06.023 fatcat:ce7mrmtvpzfbtokfhcxqdy3dp4

Good Features to Correlate for Visual Tracking

Erhan Gundogdu, A. Aydin Alatan
2018 IEEE Transactions on Image Processing  
During the recent years, correlation filters have shown dominant and spectacular results for visual object tracking.  ...  To this end, in this manuscript the problem of learning deep fully convolutional features for the CFB visual tracking is formulated.  ...  [8] has triggered the use of correlation filters for visual tracking.  ... 
doi:10.1109/tip.2018.2806280 pmid:29994635 fatcat:p4ap5ibd5ngirlk5qcdxstgv2e

Multiscale spatially regularised correlation filters for visual tracking

Xiaodong Gu, Xinyu Huang, Alade Tokuta
2017 IET Computer Vision  
In this study, the authors proposed multiscale spatially regularised correlation filters (MSRCF) for visual tracking.  ...  Correlation filters with limited boundaries and spatially regularised discriminative correlation filters were proposed to reduce boundary effects.  ...  Acknowledgment This work was supported in part by the National Science Foundation award HRD 1345219.  ... 
doi:10.1049/iet-cvi.2016.0241 fatcat:f5tsxmygtrc53iygeivllbkn4y

Deep visual nerve tracking in ultrasound images

Mohammad Alkhatib, Adel Hafiane, Pierre Vieyres, Alain Delbos
2019 Computerized Medical Imaging and Graphics  
While no deep-learning study exists for tracking the nerves in ultrasound images, this paper explores thirteen most recent deep-learning trackers for nerve tracking and presents a comparative study for  ...  Overall, deep-learning trackers provide good performance and show a comparative performance for tracking different kinds of nerves in ultrasound images.  ...  We would like to thank Region Centre Val de Loire for supporting the work.  ... 
doi:10.1016/j.compmedimag.2019.05.007 pmid:31349184 fatcat:ghqphllegvaw3knapi6tl4kgke

FuCoLoT -- A Fully-Correlational Long-Term Tracker [article]

Alan Lukežič, Luka Čehovin Zajc, Tomáš Vojíř, Jiří Matas, Matej Kristan
2019 arXiv   pre-print
A novel mechanism based on the correlation response is used for tracking failure estimation.  ...  It exploits the novel DCF constrained filter learning method to design a detector that is able to re-detect the target in the whole image efficiently.  ...  Jiří Matas and Tomáš Vojíř were supported by The Czech Science Foundation Project GACR P103/12/G084 and Toyota Motor Europe.  ... 
arXiv:1711.09594v2 fatcat:a5piigayn5dgzgfcfhghyva3za

Learning a temporally invariant representation for visual tracking

Chao Ma, Xiaokang Yang, Chongyang Zhang, Ming-Hsuan Yang
2015 2015 IEEE International Conference on Image Processing (ICIP)  
In this paper, we propose to learn temporally invariant features from a large number of image sequences to represent objects for visual tracking.  ...  We employ linear correlation filters to encode the appearance templates of targets and perform the tracking task by searching for the maximum responses at each frame.  ...  Zhang are supported in part by the NSFC Grants #61025005, #61129001 and #61221001, STCSM Grants #14XD1402100 and #13511504501, 111 Program Grant #B07022, and CNKT R&D Program Grant  ... 
doi:10.1109/icip.2015.7350921 dblp:conf/icip/MaYZY15 fatcat:tzkimbiitfaxzh4273cbxzxuye

Part-based Visual Tracking via Structural Support Correlation Filter [article]

Zhangjian Ji, Kai Feng, Yuhua Qian
2018 arXiv   pre-print
Then, our proposed model can learn the support correlation filter of each part jointly by a star structure model, which preserves the spatial layout structure among parts and tolerates outliers of parts  ...  In order to better deal with the partial occlusion issue and improve their efficiency, we propose a novel part-based structural support correlation filter tracking method, which absorbs the strong discriminative  ...  Support Correlation Filter in Nonlinear Space To make the support correlation filter (SCF) model to be extended to learn the nonlinear decision function, we now derive a "dual version" for the SCF model  ... 
arXiv:1805.09971v1 fatcat:j4eetkl7uvh4de4henze3pzrzu

The Thermal Infrared Visual Object Tracking VOT-TIR2015 Challenge Results

Michael Felsberg, Amanda Berg, Gustav Häger, Jörgen Ahlberg, Matej Kristan, Jiri Matas, Ales Leonardis, Luka Cehovin, Gustavo Fernández, Tomás Vojír, Georg Nebehay, Roman P. Pflugfelder
2015 2015 IEEE International Conference on Computer Vision Workshop (ICCVW)  
The Thermal Infrared Visual Object Tracking challenge 2015, VOT-TIR2015, aims at comparing short-term singleobject visual trackers that work on thermal infrared (TIR) sequences and do not apply pre-learned  ...  VOT-TIR2015 is the first benchmark on shortterm tracking in TIR sequences. Results of 24 trackers are presented. For each participating tracker, a short description is provided in the appendix.  ...  process for visual tracking.  ... 
doi:10.1109/iccvw.2015.86 dblp:conf/iccvw/FelsbergBHAKMLC15 fatcat:lu5tvcxj2rhede2d3kpjvz3ghy
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