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.
|Original language||English (US)|
|Title of host publication||Computer Vision – ECCV 2016 Workshops, Proceedings|
|Editors||Gang Hua, Herve Jegou|
|Number of pages||26|
|State||Published - 2016|
|Event||Computer Vision - ECCV 2016 Workshops, Proceedings - Amsterdam, Netherlands|
Duration: Oct 8 2016 → Oct 16 2016
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||Computer Vision - ECCV 2016 Workshops, Proceedings|
|Period||10/8/16 → 10/16/16|
Bibliographical noteFunding Information:
This work was supported in part by the following research programs and projects: Slovenian research agency research programs P2-0214, P2-0094, Slovenian research agency projects J2-4284, J2-3607, J2-2221 and European Union 7th Framework Programme under grant agreement 257906. J. Matas and T. Vojir were supported by CTU Project SGS13/142/OHK3/2T/13 and by the Technology Agency of the Czech Republic project TE01020415 (V3C – Visual Computing Competence Center). M. Felsberg, G. Häger, and A. Eldesokey were supported by the Wallenberg Autonomous Systems Program WASP, the Swedish Foundation for Strategic Research through the project CUAS, and the Swedish Research Council trough the project . J. Ahlberg and A. Berg were supported by the European Union 7th Framework Programme under grant agreement 312784 (P5) and the Swedish Research Council through the contract D0570301. Some experiments where run on GPUs donated by NVIDIA.
© Springer International Publishing Switzerland 2016.
- Object tracking
- Performance evaluation
- Thermal IR
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)