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The Seventh Visual Object Tracking VOT2019 Challenge Results
Univ Ljubljana, Slovenia.
Czech Tech Univ, Czech Republic.
Univ Birmingham, England.
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.ORCID-id: 0000-0002-6096-3648
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2019 (Engelska)Ingår i: 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW), IEEE COMPUTER SOC , 2019, s. 2206-2241Konferensbidrag, Publicerat paper (Refereegranskat)
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).
Ort, förlag, år, upplaga, sidor
IEEE COMPUTER SOC , 2019. s. 2206-2241
Serie
IEEE International Conference on Computer Vision Workshops, ISSN 2473-9936
Nationell ämneskategori
Datorgrafik och datorseende
Identifikatorer
URN: urn:nbn:se:liu:diva-169305DOI: 10.1109/ICCVW.2019.00276ISI: 000554591602038ISBN: 9781728150239 (digital)OAI: oai:DiVA.org:liu-169305DiVA, id: diva2:1466584
Konferens
IEEE/CVF International Conference on Computer Vision (ICCV), Seoul, SOUTH KOREA, oct 27-nov 02, 2019
Anmärkning

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

Tillgänglig från: 2020-09-12 Skapad: 2020-09-12 Senast uppdaterad: 2025-02-07Bibliografiskt granskad

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Felsberg, MichaelBerg, AmandaEldesokey, AbdelrahmanKhan, Fahad Shahbaz

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