liu.seSearch for publications in DiVA
EnglishSvenskaNorsk
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
The Seventh Visual Object Tracking VOT2019 Challenge Results
Univ Ljubljana, Slovenia.
Czech Tech Univ, Czech Republic.
Univ Birmingham, England.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-6096-3648
Show others and affiliations
2019 (English)In: 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW), IEEE COMPUTER SOC , 2019, p. 2206-2241Conference paper, Published paper (Refereed)
Abstract [en]

The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2019 focused on long-term tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard short-term, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website(1).
Place, publisher, year, edition, pages
IEEE COMPUTER SOC , 2019. p. 2206-2241
Series
IEEE International Conference on Computer Vision Workshops, ISSN 2473-9936
National Category
Computer graphics and computer vision
Identifiers
URN: urn:nbn:se:liu:diva-169305DOI: 10.1109/ICCVW.2019.00276ISI: 000554591602038ISBN: 9781728150239 (electronic)OAI: oai:DiVA.org:liu-169305DiVA, id: diva2:1466584
Conference
IEEE/CVF International Conference on Computer Vision (ICCV), Seoul, SOUTH KOREA, oct 27-nov 02, 2019
Note

Funding Agencies|Slovenian research agencySlovenian Research Agency - Slovenia [J2-8175, P2-0214, P2-0094]; Czech Science Foundation Project GACR [P103/12/G084]; MURI project - MoD/DstlMURI; EPSRCEngineering & Physical Sciences Research Council (EPSRC) [EP/N019415/1]; WASP; VR (ELLIIT, LAST, and NCNN); SSF (SymbiCloud); AIT Strategic Research Programme; Faculty of Computer Science, University of Ljubljana, Slovenia

Available from: 2020-09-12 Created: 2020-09-12 Last updated: 2025-02-07Bibliographically approved

Open Access in DiVA

fulltext(3165 kB)1142 downloads
File information
File name FULLTEXT01.pdfFile size 3165 kBChecksum SHA-512
e051006ce25c9bd2ace6dc9edaed3dd2065d36a2667737881968311e56331751de951da7ee7a9db785873264f3185d00729c98e066b1176b840fd695fa137b8c
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Authority records

Felsberg, MichaelBerg, AmandaEldesokey, AbdelrahmanKhan, Fahad Shahbaz

Search in DiVA

By author/editor
Felsberg, MichaelBerg, AmandaEldesokey, AbdelrahmanKhan, Fahad Shahbaz
By organisation
Computer VisionFaculty of Science & Engineering
Computer graphics and computer vision

Search outside of DiVA

GoogleGoogle Scholar
Total: 1156 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 489 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
v. 2.47.0
|
Accessibility
|
DiVA portal
|
DiVA Log in
|
Contact us
|
LiU University Library
|
SwePub
|
Uppsök