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The Visual Object Tracking VOT2015 Challenge Results
University of Ljubljana, Slovenia.
Czech Technical University, Czech Republic.
University of Birmingham, United Kingdom.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0002-6096-3648
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Number of Authors: 135
2015 (English)In: Proceedings 2015 IEEE International Conference on Computer Vision Workshops ICCVW 2015, IEEE , 2015, 564-586 p.Conference paper (Refereed)Text
Abstract [en]

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. Results of 62 trackers are presented. The number of tested trackers makes VOT 2015 the largest benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the appendix. Features of the VOT2015 challenge that go beyond its VOT2014 predecessor are: (i) a new VOT2015 dataset twice as large as in VOT2014 with full annotation of targets by rotated bounding boxes and per-frame attribute, (ii) extensions of the VOT2014 evaluation methodology by introduction of a new performance measure. The dataset, the evaluation kit as well as the results are publicly available at the challenge website.

Place, publisher, year, edition, pages
IEEE , 2015. 564-586 p.
, IEEE International Conference on Computer Vision Workshop (ICCVW), ISSN 5499 ; 2015
Keyword [en]
Area measurement;Australia;Benchmark testing;Object tracking;Performance evaluation;Target tracking;Visualization
National Category
Computer Vision and Robotics (Autonomous Systems) Radiology, Nuclear Medicine and Medical Imaging Signal Processing
URN: urn:nbn:se:liu:diva-125253DOI: 10.1109/ICCVW.2015.79ISI: 000380434700070ISBN: 978-1-4673-8390-5OAI: diva2:904096
2015 IEEE International Conference on Computer Vision Workshops, 11–18 December 2015, Santiago, Chile
Available from: 2016-02-18 Created: 2016-02-18 Last updated: 2016-08-26Bibliographically approved

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Felsberg, MichaelHäger, Gustav
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Computer VisionFaculty of Science & EngineeringCenter for Medical Image Science and Visualization (CMIV)
Computer Vision and Robotics (Autonomous Systems)Radiology, Nuclear Medicine and Medical ImagingSignal Processing

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