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The Thermal Infrared Visual Object Tracking VOT-TIR2016 Challenge Results
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.ORCID-id: 0000-0002-6096-3648
University of Ljubljana, Slovenia.
Czech Technical University, Czech Republic.
University of Birmingham, England.
Vise andre og tillknytning
2016 (engelsk)Inngår i: Computer Vision – ECCV 2016 Workshops. ECCV 2016. / [ed] Hua G., Jégou H., SPRINGER INT PUBLISHING AG , 2016, s. 824-849Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The Thermal Infrared Visual Object Tracking challenge 2016, VOT-TIR2016, aims at comparing short-term single-object visual trackers that work on thermal infrared (TIR) sequences and do not apply pre-learned models of object appearance. VOT-TIR2016 is the second benchmark on short-term tracking in TIR sequences. Results of 24 trackers are presented. For each participating tracker, a short description is provided in the appendix. The VOT-TIR2016 challenge is similar to the 2015 challenge, the main difference is the introduction of new, more difficult sequences into the dataset. Furthermore, VOT-TIR2016 evaluation adopted the improvements regarding overlap calculation in VOT2016. Compared to VOT-TIR2015, a significant general improvement of results has been observed, which partly compensate for the more difficult sequences. The dataset, the evaluation kit, as well as the results are publicly available at the challenge website.
sted, utgiver, år, opplag, sider
SPRINGER INT PUBLISHING AG , 2016. s. 824-849
Serie
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 9914
Emneord [en]
Performance evaluation; Object tracking; Thermal IR; VOT
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-133773DOI: 10.1007/978-3-319-48881-3_55ISI: 000389501700055ISBN: 978-3-319-48881-3 (digital)ISBN: 978-3-319-48880-6 (tryckt)OAI: oai:DiVA.org:liu-133773DiVA, id: diva2:1063949
Konferanse
14th European Conference on Computer Vision (ECCV)
Tilgjengelig fra: 2017-01-11 Laget: 2017-01-09 Sist oppdatert: 2025-02-07

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Felsberg, MichaelBerg, AmandaEldesokey, AbdelrahmanAhlberg, JörgenKhan, Fahad ShahbazDanelljan, Martin

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