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The Visual Object Tracking VOT2014 Challenge Results
[chapter]
<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>
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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 ...
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The Visual Object Tracking VOT2013 Challenge Results
<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>
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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 ...
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Visual Tracking Based on Complementary Learners with Distractor Handling
<span title="">2017</span>
<i title="Hindawi Limited">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wpareqynwbgqdfodcyhh36aqaq" style="color: black;">Mathematical Problems in Engineering</a>
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The representation of the object is an important factor in building a robust visual object tracking algorithm. ...
This decision depends on the result obtained from the distractor detection process. Experiments were performed on the widely used VOT2014 and VOT2015 benchmark datasets. ...
Several decades ago, to solve challenging problems in visual tracking, researchers used a color histogram [1] to represent the target object. ...
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Visual Object Tracking Fusing CNN and Color Histogram based Tracker and Depth Estimation for Automatic Immersive Audio Mixing
<span title="2020-03-31">2020</span>
<i title="Korean Society for Internet Information (KSII)">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hupfbobgkvepdnt5g32qxkypsy" style="color: black;">KSII Transactions on Internet and Information Systems</a>
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We propose a robust visual object tracking algorithm fusing a convolutional neural network tracker trained offline from a large number of video repositories and a color histogram based tracker to track ...
Our proposed algorithm demonstrates about 2% improved accuracy over the outperforming GOTURN algorithm in the existing VOT2014 tracking benchmark. ...
Results As a test data set, we used VOT2014 benchmark with 25 video sequences used in the Visual Object Tracking VOT2014 Challenge [28] . ...
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Learning Multi-domain Convolutional Neural Networks for Visual Tracking
<span title="">2016</span>
<i title="IEEE">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ilwxppn4d5hizekyd3ndvy2mii" style="color: black;">2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)</a>
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We propose a novel visual tracking algorithm based on the representations from a discriminatively trained Convolutional Neural Network (CNN). ...
Online tracking is performed by evaluating the candidate windows randomly sampled around the previous target state. ...
Acknowledgements This work was partly supported by IITP grant (B0101-16-0307; Machine Learning Center, B0101-16-0552; Deep-View) funded by the Korean government (MSIP). ...
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Learning Multi-Domain Convolutional Neural Networks for Visual Tracking
[article]
<span title="2016-01-06">2016</span>
<i >
arXiv
</i>
<span class="release-stage" >pre-print</span>
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<span title="2015-10-27">2015</span>
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We propose a novel visual tracking algorithm based on the representations from a discriminatively trained Convolutional Neural Network (CNN). ...
Online tracking is performed by evaluating the candidate windows randomly sampled around the previous target state. ...
: Object Tracking Benchmark [40] and VOT2014 [25] . ...
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Robust visual tracking using template anchors
<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>
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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 ...
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Patch-based adaptive weighting with segmentation and scale (PAWSS) for visual tracking
[article]
<span title="2017-08-03">2017</span>
<i >
arXiv
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<span class="release-stage" >pre-print</span>
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Experimentally, we evaluate our approach on the online tracking benchmark (OTB) dataset and Visual Object Tracking (VOT) challenge datasets. ...
Tracking-by-detection algorithms are widely used for visual tracking, where the problem is treated as a classification task where an object model is updated over time using online learning techniques. ...
The work was supported by the EP-SRC (EP/N013220/1, EP/N022750/1, EP/N027078/1, NS/A000027/1, EP/P012841/1), The Wellcome Trust (WT101957, 201080/Z/16/Z) and the EU-Horizon2020 project EndoVESPA (H2020 ...
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Online Object Tracking with Proposal Selection
[article]
<span title="2015-09-30">2015</span>
<i >
arXiv
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<span class="release-stage" >pre-print</span>
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We extensively evaluate our approach on the visual object tracking 2014 challenge and online tracking benchmark datasets, and show the best performance. ...
Tracking-by-detection approaches are some of the most successful object trackers in recent years. ...
This work was supported in part by the MSR-Inria joint project, Google Faculty Research Award, and the ERC advanced grant ALLEGRO. ...
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A Visual Tracking Algorithm in Large-Scale Video with Convolutional Neural Networks
<span title="2018-06-25">2018</span>
<i title="NeuroQuantology Journal">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vfjjshkdo5eynaqtxbx53v4cy4" style="color: black;">NeuroQuantology</a>
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The algorithm can track the trajectory of a moving object in a video with complex background quite precisely. ...
Experiment results show that performance of the proposed algorithm is excellent for some representative tracking benchmarks. ...
Acknowledgments Authors gratefully thank the co-workers for concerning the research project and also acknowledge the support of Research Fund of Shaanxi Provincial Education Department (Grant No. 17JK0710 ...
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Online Object Tracking with Proposal Selection
<span title="">2015</span>
<i title="IEEE">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/753trptklbb4nj6jquqadzwwdu" style="color: black;">2015 IEEE International Conference on Computer Vision (ICCV)</a>
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We extensively evaluate our approach on the visual object tracking 2014 challenge and online tracking benchmark datasets, and show the best performance. * ...
Tracking-by-detection approaches are some of the most successful object trackers in recent years. ...
This work was supported in part by the MSR-Inria joint project, Google Faculty Research Award, and the ERC advanced grant ALLEGRO. ...
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Multi-template Scale-Adaptive Kernelized Correlation Filters
<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>
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We validate the efficacy of our approach on two tracking datasets, VOT2014 and VOT2015. ...
These drawbacks include an assumed fixed scale of the target in every frame, as well as, a heuristic update strategy of the filter taps to incorporate historical tracking information (i.e. simple linear ...
KCF has achieved impressive results on the visual tracking benchmark [24] and ranked third in the VOT2014 challenge [14] achieving real-time performance. ...
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The Visual Object Tracking VOT2017 Challenge Results
<span title="">2017</span>
<i title="IEEE">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6s36fqp6q5hgpdq2scjq3sfu6a" style="color: black;">2017 IEEE International Conference on Computer Vision Workshops (ICCVW)</a>
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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 ...
This paper discusses the VOT2015 challenge organized in conjunction with the ICCV2015 Visual object tracking workshop and the results obtained. ...
Videos (ALOV) [61] and the Visual object tracking challenge (VOT) [38, 36, 34] . ...
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Fully Convolutional Single-Crop Siamese Networks for Real-Time Visual Object Tracking
<span title="2019-09-24">2019</span>
<i title="MDPI AG">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ikdpfme5h5egvnwtvvtjrnntyy" style="color: black;">Electronics</a>
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The visual object tracking problem seeks to track an arbitrary object in a video, and many deep convolutional neural network-based algorithms have achieved significant performance improvements in recent ...
This paper presents a single-crop visual object tracking algorithm based on a fully convolutional Siamese network (SiamFC). ...
The visual object tracking problem is challenging because the appearance of the target object is given in the first frame only. ...
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Tracker Fusion on VOT Challenge: How Does It Perform and What Can We Learn about Single Trackers?
<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>
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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). ...
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