The Thermal Infrared Visual Object Tracking VOT-TIR2016 Challenge Results

Felsberg, Michael; Kristan, Matej; Matas, Jiri; Leonardis, Ales; Pflugfelder, Roman; Häger, Gustav; Berg, Amanda; Eldesokey, Abdelrahman; Ahlberg, Jörgen; Cehovin, Luka; Vojir, Tomas; Lukezic, Alan; Fernandez, Gustavo; Petrosino, Alfredo; Garcia-Martin, Alvaro; Solis Montero, Andres; Varfolomieiev, Anton; Erdem, Aykut; Han, Bohyung; Chang, Chang-Ming; Du, Dawei; Erdem, Erkut; Khan, Fahad Shahbaz; Porikli, Fatih; Zhao, Fei; Bunyak, Filiz; Battistone, Francesco; Zhu, Gao; Seetharaman, Guna; Li, Hongdong; Qi, Honggang; Bischof, Horst; Possegger, Horst; Nam, Hyeonseob; Valmadre, Jack; Zhu, Jianke; Feng, Jiayi; Lang, Jochen; Martinez, Jose M.; Palaniappan, Kannappan; Lebeda, Karel; Gao, Ke; Mikolajczyk, Krystian; Wen, Longyin; Bertinetto, Luca; Poostchi, Mahdieh; Maresca, Mario; Danelljan, Martin; Arens, Michael; Tang, Ming; Baek, Mooyeol; Fan, Nana; Al-Shakarji, Noor; Miksik, Ondrej; Akin, Osman; Torr, Philip H. S.; Huang, Qingming; Martin-Nieto, Rafael; Pelapur, Rengarajan; Bowden, Richard; Laganiere, Robert; Krah, Sebastian B.; Li, Shengkun; Yao, Shizeng; Hadfield, Simon; Lyu, Siwei; Becker, Stefan; Golodetz, Stuart; Hu, Tao; Mauthner, Thomas; Santopietro, Vincenzo; Li, Wenbo; Huebner, Wolfgang; Li, Xin; Li, Yang; Xu, Zhan; He, Zhenyu

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The Thermal Infrared Visual Object Tracking VOT-TIR2016 Challenge Results

Felsberg, Michael

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

Kristan, Matej

University of Ljubljana, Slovenia.

Matas, Jiri

Czech Technical University, Czech Republic.

Leonardis, Ales

University of Birmingham, England.

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2016 (English)In: Computer Vision – ECCV 2016 Workshops. ECCV 2016. / [ed] Hua G., Jégou H., SPRINGER INT PUBLISHING AG , 2016, p. 824-849Conference paper, Published paper (Refereed)

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.

Place, publisher, year, edition, pages

SPRINGER INT PUBLISHING AG , 2016. p. 824-849

Series

Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 9914

Keywords [en]

Performance evaluation; Object tracking; Thermal IR; VOT

National Category

Computer graphics and computer vision

Identifiers

URN: urn:nbn:se:liu:diva-133773DOI: 10.1007/978-3-319-48881-3_55ISI: 000389501700055ISBN: 978-3-319-48881-3 (electronic)ISBN: 978-3-319-48880-6 (print)OAI: oai:DiVA.org:liu-133773DiVA, id: diva2:1063949

Conference

14th European Conference on Computer Vision (ECCV)

Available from: 2017-01-11 Created: 2017-01-09 Last updated: 2025-02-07

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Felsberg, Michael Berg, Amanda Eldesokey, Abdelrahman Ahlberg, Jörgen Khan, Fahad Shahbaz Danelljan, Martin

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