Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
The Sixth Visual Object Tracking VOT2018 Challenge Results
University of Ljubljana, Slovenia.
University of Birmingham, United Kingdom.
Czech Technical University, Czech Republic.
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.ORCID-id: 0000-0002-6096-3648
Vise andre og tillknytning
2018 (engelsk)Inngår i: Computer Vision – ECCV 2018 Workshops: Munich, Germany, September 8–14, 2018 Proceedings, Part I / [ed] Laura Leal-Taixé and Stefan Roth, Cham: Springer Publishing Company, 2018, s. 3-53Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty 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 and a “real-time” experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. A long-term tracking subchallenge has been introduced to the set of standard VOT sub-challenges. The new subchallenge focuses on long-term tracking properties, namely coping with target disappearance and reappearance. A new dataset has been compiled and a performance evaluation methodology that focuses on long-term tracking capabilities has been adopted. The VOT toolkit has been updated to support both standard short-term and the new long-term tracking subchallenges. 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 (http://votchallenge.net).

sted, utgiver, år, opplag, sider
Cham: Springer Publishing Company, 2018. s. 3-53
Serie
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 11129
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-161343DOI: 10.1007/978-3-030-11009-3_1ISBN: 9783030110086 (tryckt)ISBN: 9783030110093 (digital)OAI: oai:DiVA.org:liu-161343DiVA, id: diva2:1366619
Konferanse
Computer Vision – ECCV 2018 Workshops, Munich, Germany, September 8–14, 2018
Tilgjengelig fra: 2019-10-30 Laget: 2019-10-30 Sist oppdatert: 2020-01-22bibliografisk kontrollert

Open Access i DiVA

The Sixth Visual Object Tracking VOT2018 Challenge Results(1596 kB)29 nedlastinger
Filinformasjon
Fil FULLTEXT01.pdfFilstørrelse 1596 kBChecksum SHA-512
5996f25df8331523743e5aaeb1ce0ac6c4337dec34744d57b3f17f1a98d57965e437d7f200ef4f772a5df5c0fc9a2e94dca2ce3b98e05455373d3624102ea2cd
Type fulltextMimetype application/pdf

Andre lenker

Forlagets fulltekst

Søk i DiVA

Av forfatter/redaktør
Felsberg, MichaelBhat, GoutamEldesokey, AbdelrahmanKhan, Fahad ShahbazJohnander, JoakimDanelljan, Martin
Av organisasjonen

Søk utenfor DiVA

GoogleGoogle Scholar
Totalt: 29 nedlastinger
Antall nedlastinger er summen av alle nedlastinger av alle fulltekster. Det kan for eksempel være tidligere versjoner som er ikke lenger tilgjengelige

doi
isbn
urn-nbn

Altmetric

doi
isbn
urn-nbn
Totalt: 46 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf