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The Visual Object Tracking VOT2013 Challenge Results

Matej Kristan, Roman Pflugfelder, Ale Leonardis, Jiri Matas, Fatih Porikli, Luka Cehovin, Georg Nebehay, Gustavo Fernandez, Toma Vojir, Adam Gatt, Ahmad Khajenezhad, Ahmed Salahledin (+39 others)
<span title="">2013</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6s36fqp6q5hgpdq2scjq3sfu6a" style="color: black;">2013 IEEE International Conference on Computer Vision Workshops</a> </i> &nbsp;
The Visual Object Tracking challenge 2014, VOT2014, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance.  ...  The dataset, the evaluation kit as well as the results are publicly available at the challenge website 25 .  ...  Acknowledgements This work was supported in part by the following research programs and projects: Slovenian research agency projects J24284, J23607 and J2-2221 and European 34 We consider the Structured  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccvw.2013.20">doi:10.1109/iccvw.2013.20</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/iccvw/KristanPLMPCNFV13.html">dblp:conf/iccvw/KristanPLMPCNFV13</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2kq3duucy5evvcs43mme3v6ocu">fatcat:2kq3duucy5evvcs43mme3v6ocu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20160806192310/http://www.cbsr.ia.ac.cn:80/users/lywen/papers/VOT2014.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3e/62/3e62a4c02c5472984502cbb78439d0bce47c3cb0.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccvw.2013.20"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Robust visual tracking using template anchors

Luka Cehovin, Ales Leonardis, Matej Kristan
<span title="">2016</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wsjivbkuezdvxdnrhihbwjrxlu" style="color: black;">2016 IEEE Winter Conference on Applications of Computer Vision (WACV)</a> </i> &nbsp;
We have implemented a new visual tracker according to the proposed that achieves a state-of-the-art performance on two recent, highly challenging, visual object tracking benchmarks VOT2013 [16] and VOT2014  ...  The datasets consist of 16 (VOT2013) and 25 (VOT2014) manually annotated sequences that contain various challenging visual tracking scenarios such as severe illumination changes, object deformations, abrupt  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/wacv.2016.7477570">doi:10.1109/wacv.2016.7477570</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/wacv/CehovinLK16.html">dblp:conf/wacv/CehovinLK16</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gdc5d3q7nnaspicfb5lvxtpjce">fatcat:gdc5d3q7nnaspicfb5lvxtpjce</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200311032659/https://research.birmingham.ac.uk/portal/files/27840700/Cehovin_et_al_Visual_tracking_using_anchor_templates.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/27/da/27da38062d12db36e949b403c9179bba83b3b014.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/wacv.2016.7477570"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Using Discriminative Motion Context for Online Visual Object Tracking

Stefan Duffner, Christophe Garcia
<span title="">2016</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jqw2pm7kwvhchpdxpcm5ryoic4" style="color: black;">IEEE transactions on circuits and systems for video technology (Print)</a> </i> &nbsp;
Moreover, we present quantitative and qualitative results on four challenging public datasets that show the robustness of the tracking algorithm with respect to appearance and view changes, lighting variations  ...  In this paper, we propose an algorithm for on-line, real-time tracking of arbitrary objects in videos from unconstrained environments.  ...  This dataset has also been used by [11] and partially by [8] among others. 3) VOT2013: The third dataset 3 has been used for the Visual Object Tracking (VOT) Challenge 2013 [48] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tcsvt.2015.2504739">doi:10.1109/tcsvt.2015.2504739</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/aena2ndc2nf75bfokisroulzju">fatcat:aena2ndc2nf75bfokisroulzju</a> </span>
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Revisiting Robust Visual Tracking Using Pixel-Wise Posteriors [chapter]

Falk Schubert, Daniele Casaburo, Dirk Dickmanns, Vasileios Belagiannis
<span title="">2015</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
The impressive results help promoting segmentation-based tracking algorithms, which are currently under-represented in the visual tracking benchmarks.  ...  Last, but not least, we discuss implementation details to speed up the computation by using only a sparse set of pixels for the propagation of the contour, which results in tracking speed of up to 200Hz  ...  Acknowledgments We thank Esther Horbert (Computer Vision Group RWTH Aachen University) for providing four evaluation sequences and valuable feedback for resolving open questions on the hidden details of  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-20904-3_26">doi:10.1007/978-3-319-20904-3_26</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hnjzlnvoyndpjnrwalgwvxt7ze">fatcat:hnjzlnvoyndpjnrwalgwvxt7ze</a> </span>
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Classifying Global Scene Context for On-line Multiple Tracker Selection

Salma Moujtahid, Stefan Duffner, Atilla Baskurt
<span title="">2015</span> <i title="British Machine Vision Association"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6bfo5625nvdfvbgyf7ldi5wmfe" style="color: black;">Procedings of the British Machine Vision Conference 2015</a> </i> &nbsp;
The objective is to select at each frame the best tracker, i.e. the one that outputs the bounding box that fits best the object to track.  ...  Finally, a Kalman Filter is applied as a post-processing step to temporally smooth the resulting object bounding box B s t from the selected trackers T s .  ...  We evaluated the performance of our framework on the Visual Object Tracking (VOT2013) benchmark [4] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5244/c.29.163">doi:10.5244/c.29.163</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/bmvc/MoujtahidDB15.html">dblp:conf/bmvc/MoujtahidDB15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/az5zrsfq7ngavok7m3nnm76u6y">fatcat:az5zrsfq7ngavok7m3nnm76u6y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180720044602/http://www.bmva.org/bmvc/2015/papers/paper163/abstract163.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/cd/d7/cdd7aa0b7cf74bd695bbf51ec19eae247a69e71b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5244/c.29.163"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

BACKGROUND NORMALIZATION AND TEXTURE PATTERN-BASED VIDEO SEGMENTATION FOR VISUAL TRACKING

V Rajagopal, B Sankaragomathi
<span title="2017-12-19">2017</span> <i title="Moksha Publishing House"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kpsqayfwzzg5rccbq2sag5slha" style="color: black;">International Research Journal of Pharmacy</a> </i> &nbsp;
Visual tracking is the task of estimating the path of a target object in each frame of the video. Various tracking approaches are developed for tracking the position of the target.  ...  The experimental result proves that the proposed approach yields better precision, recall and F-score performance than the existing tracking approaches.  ...  The VOT2013 challenge benchmark includes 16 short video sequences that show various objects in the challenging backgrounds.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.7897/2230-8407.0811239">doi:10.7897/2230-8407.0811239</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vbcgn5oiarcttd56g3nwnijyri">fatcat:vbcgn5oiarcttd56g3nwnijyri</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180127100100/http://www.irjponline.com:80/admin/php/uploads/2845_pdf.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/75/06/75066a4a5f3678fd54d17f9493ab80fc252fa8ea.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.7897/2230-8407.0811239"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Coherent Selection of Independent Trackers for Real-time Object Tracking

Salma Moujtahid, Stefan Duffner, Atilla Baskurt
<span title="">2015</span> <i title="SCITEPRESS - Science and and Technology Publications"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tyl5kfigejfehnouax7r3tii24" style="color: black;">Proceedings of the 10th International Conference on Computer Vision Theory and Applications</a> </i> &nbsp;
This paper presents a new method for combining several independent and heterogeneous tracking algorithms for the task of online single-object tracking.  ...  Moreover, the proposed approach is able to switch between different tracking methods when the scene conditions or the object appearance rapidly change.  ...  VOT2013 is a visual object tracking challenge held in 2013 in order to benchmark on-line tracking algorithms. The data set contains 23 videos and 8416 frames.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5220/0005311305840592">doi:10.5220/0005311305840592</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/visapp/MoujtahidDB15.html">dblp:conf/visapp/MoujtahidDB15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/v5graxbqq5edvi52ayni5ulhym">fatcat:v5graxbqq5edvi52ayni5ulhym</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200709090600/https://liris.cnrs.fr/Documents/Liris-7024.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/2c/4b/2c4b5c4940322641b4eabaa1f6483750655b3ddb.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5220/0005311305840592"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Exploiting Contextual Motion Cues for Visual Object Tracking [chapter]

Stefan Duffner, Christophe Garcia
<span title="">2015</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
Finally, we present quantitative and qualitative results on four challenging public datasets that show the robustness of the tracking algorithm with respect to appearance and view changes, lighting variations  ...  The method is based on a particle filter framework using different visual features and motion prediction models.  ...  VOT2013 3 is the Visual Object Tracking (VOT) Benchmark 2013 [11] containing 16 videos that show a large variability in terms of camera motion, illumination change, occlusion, object size, and motion  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-16181-5_16">doi:10.1007/978-3-319-16181-5_16</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jmii6tj6iffw5f2zyptbabgate">fatcat:jmii6tj6iffw5f2zyptbabgate</a> </span>
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The Matrioska Tracking Algorithm on LTDT2014 Dataset

Mario Edoardo Maresca, Alfredo Petrosino
<span title="">2014</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ilwxppn4d5hizekyd3ndvy2mii" style="color: black;">2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops</a> </i> &nbsp;
for the evaluation of single-object long-term visual trackers.  ...  Matrioska follows the approach of tracking by detection: the detector localizes the target object in each frame, using multiple keypoint-based methods.  ...  We also reported the results obtained for the VOT2013 challenge aimed to benchmark short-term trackers.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvprw.2014.128">doi:10.1109/cvprw.2014.128</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cvpr/MarescaP14.html">dblp:conf/cvpr/MarescaP14</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/t54swoxpdjaq7n3vzkr6sdzydm">fatcat:t54swoxpdjaq7n3vzkr6sdzydm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20140722122749/http://www.cv-foundation.org:80/openaccess/content_cvpr_workshops_2014/W18/papers/Maresca_The_Matrioska_Tracking_2014_CVPR_paper.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3e/35/3e358e32a1be4018c426e46eae700accbd7cccfd.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvprw.2014.128"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

DeepTrack: Learning Discriminative Feature Representations Online for Robust Visual Tracking

Hanxi Li, Yi Li, Fatih Porikli
<span title="">2016</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dhlhr4jqkbcmdbua2ca45o7kru" style="color: black;">IEEE Transactions on Image Processing</a> </i> &nbsp;
In this work, we present an efficient and very robust tracking algorithm using a single Convolutional Neural Network (CNN) for learning effective feature representations of the target object, in a purely  ...  Equipped with this novel updating algorithm, the CNN model is robust to some long-existing difficulties in visual tracking such as occlusion or incorrect detections, without loss of the effective adaption  ...  Comparison results on the VOT2013 benchmark The VOT2013 Challenge Benchmark [27] provides an evaluation kit and the dataset with 16 fully annotated sequences for evaluating tracking algorithms in realistic  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tip.2015.2510583">doi:10.1109/tip.2015.2510583</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/26841390">pmid:26841390</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nc6um7ijdndmnbuk3x4mahkx44">fatcat:nc6um7ijdndmnbuk3x4mahkx44</a> </span>
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Tracker Fusion on VOT Challenge: How Does It Perform and What Can We Learn about Single Trackers?

Christian Bailer, Didier Stricker
<span title="">2015</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6s36fqp6q5hgpdq2scjq3sfu6a" style="color: black;">2015 IEEE International Conference on Computer Vision Workshop (ICCVW)</a> </i> &nbsp;
Tracker fusion i.e. the fusion of the outputs of different tracking methods is an interesting new concept. Thus it should also be considered in the VOT challenges.  ...  It allows us for example to identify trackers that could despite poor average performance be interesting for research in object tracking.  ...  Acknowledgements This work was partially funded by the BMBF project DYNAMICS (01IW15003).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccvw.2015.85">doi:10.1109/iccvw.2015.85</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/iccvw/BailerS15.html">dblp:conf/iccvw/BailerS15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4tergjiuqjh2xco57p6i4r5dl4">fatcat:4tergjiuqjh2xco57p6i4r5dl4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809084853/http://www.cv-foundation.org/openaccess/content_iccv_2015_workshops/w14/papers/Bailer_Tracker_Fusion_on_ICCV_2015_paper.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/96/7e/967e38e499ccfaf5e3abbb718d76daaf6b034b92.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccvw.2015.85"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

The Visual Object Tracking VOT2014 Challenge Results [chapter]

Matej Kristan, Roman Pflugfelder, Aleš Leonardis, Jiri Matas, Luka Čehovin, Georg Nebehay, Tomáš Vojíř, Gustavo Fernández, Alan Lukežič, Aleksandar Dimitriev, Alfredo Petrosino, Amir Saffari (+45 others)
<span title="">2015</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance.  ...  The dataset, the evaluation kit as well as the results are publicly available at the challenge website 1 .  ...  Acknowledgements This work was supported in part by the following research programs and projects: Slovenian research agency research programs P2-0214, P2-0094, Slovenian research agency projects J2-4284  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-16181-5_14">doi:10.1007/978-3-319-16181-5_14</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oawrb5vmxvdeji675oyluf3dym">fatcat:oawrb5vmxvdeji675oyluf3dym</a> </span>
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The Visual Object Tracking VOT2015 Challenge Results

Matej Kristan, Jiri Matas, Ales Leonardis, Michael Felsberg, Luka Cehovin, Gustavo Fernández, Tomás Vojír, Gustav Häger, Georg Nebehay, Roman P. Pflugfelder
<span title="">2015</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6s36fqp6q5hgpdq2scjq3sfu6a" style="color: black;">2015 IEEE International Conference on Computer Vision Workshop (ICCVW)</a> </i> &nbsp;
The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative.  ...  The dataset, the evaluation kit and the results are publicly available at the challenge website 1 .  ...  This paper presents the VOT2017 challenge, organized in conjunction with the ICCV2017 Visual Object Tracking workshop, and the results obtained.  ... 
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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
<span title="">2015</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6s36fqp6q5hgpdq2scjq3sfu6a" style="color: black;">2015 IEEE International Conference on Computer Vision Workshop (ICCVW)</a> </i> &nbsp;
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  ...  The VOT-TIR2015 challenge is based on the VOT2013 challenge, but introduces the following novelties: (i) the newly collected LTIR (Linköping TIR) dataset is used, (ii) the VOT2013 attributes are adapted  ...  This paper describes the first thermal infrared (TIR), short-term tracking challenge, the Visual Object Tracking TIR (VOT-TIR2015) challenge, and the results obtained.  ... 
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Transfer Learning Based Visual Tracking with Gaussian Processes Regression [chapter]

Jin Gao, Haibin Ling, Weiming Hu, Junliang Xing
<span title="">2014</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
Modeling the target appearance is critical in many modern visual tracking algorithms.  ...  The auxiliary samples are dynamically re-weighted by the regression, and the final tracking result is determined by fusing decisions from two individual trackers, one derived from the auxiliary samples  ...  Experiment 3: VOT2013 Challenge Benchmark The visual object tracking VOT2013 Challenge Benchmark [16] provides an evaluation kit and the dataset with 16 fully annotated sequences for evaluating tracking  ... 
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