The Thermal Infrared Visual Object Tracking VOT-TIR2016 Challenge Results (bibtex)
by Michael Felsberg, Matej Kristan, Jiři Matas, Aleš Leonardis, Roman Pflugfelder, Gustav Häger, Amanda Berg, Abdelrahman Eldesokey, Jörgen Ahlberg, Luka Čehovin, Tomáš Vojír, Alan Lukežič, Gustavo Fernández, Alfredo Petrosino, Alvaro Garcia-Martin, Andrés Solís Montero, Anton Varfolomieiev, Aykut Erdem, Bohyung Han, Chang-Ming Chang, Dawei Du, Erkut Erdem, Fahad Shahbaz Khan, Fatih Porikli, Fei Zhao, Filiz Bunyak, Francesco Battistone, Gao Zhu, Guna Seetharaman, Hongdong Li, Honggang Qi, Horst Bischof, Horst Possegger, Hyeonseob Nam, Jack Valmadre, Jianke Zhu, Jiayi Feng, Jochen Lang, Jose M. Martinez, Kannappan Palaniappan, Karel Lebeda, Ke Gao, Krystian Mikolajczyk, Longyin Wen, Luca Bertinetto, Mahdieh Poostchi, Mario Maresca, Martin Danelljan, Michael Arens, Ming Tang, Mooyeol Baek, Nana Fan, Noor Al-Shakarji, Ondrej Miksik, Osman Akin, Philip H. S. Torr, Qingming Huang, Rafael Martin-Nieto, Rengarajan Pelapur, Richard Bowden, Robert Laganière, Sebastian B. Krah, Shengkun Li, Shizeng Yao, Simon Hadfield, Siwei Lyu, Stefan Becker, Stuart Golodetz, Tao Hu, Thomas Mauthner, Vincenzo Santopietro, Wenbo Li, Wolfgang Hübner, Xin Li, Yang Li, Zhan Xu, Zhenyu He
Abstract:
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.
Reference:
The Thermal Infrared Visual Object Tracking VOT-TIR2016 Challenge Results (Michael Felsberg, Matej Kristan, Jiři Matas, Aleš Leonardis, Roman Pflugfelder, Gustav Häger, Amanda Berg, Abdelrahman Eldesokey, Jörgen Ahlberg, Luka Čehovin, Tomáš Vojír, Alan Lukežič, Gustavo Fernández, Alfredo Petrosino, Alvaro Garcia-Martin, Andrés Solís Montero, Anton Varfolomieiev, Aykut Erdem, Bohyung Han, Chang-Ming Chang, Dawei Du, Erkut Erdem, Fahad Shahbaz Khan, Fatih Porikli, Fei Zhao, Filiz Bunyak, Francesco Battistone, Gao Zhu, Guna Seetharaman, Hongdong Li, Honggang Qi, Horst Bischof, Horst Possegger, Hyeonseob Nam, Jack Valmadre, Jianke Zhu, Jiayi Feng, Jochen Lang, Jose M. Martinez, Kannappan Palaniappan, Karel Lebeda, Ke Gao, Krystian Mikolajczyk, Longyin Wen, Luca Bertinetto, Mahdieh Poostchi, Mario Maresca, Martin Danelljan, Michael Arens, Ming Tang, Mooyeol Baek, Nana Fan, Noor Al-Shakarji, Ondrej Miksik, Osman Akin, Philip H. S. Torr, Qingming Huang, Rafael Martin-Nieto, Rengarajan Pelapur, Richard Bowden, Robert Laganière, Sebastian B. Krah, Shengkun Li, Shizeng Yao, Simon Hadfield, Siwei Lyu, Stefan Becker, Stuart Golodetz, Tao Hu, Thomas Mauthner, Vincenzo Santopietro, Wenbo Li, Wolfgang Hübner, Xin Li, Yang Li, Zhan Xu, Zhenyu He), In Proceedings, European Conference on Computer Vision (ECCV) workshops, 2016.
Bibtex Entry:
@InProceedings{Hadfield16e,
  Title                    = {The Thermal Infrared Visual Object Tracking VOT-TIR2016 Challenge Results},
  Author                   = {Michael Felsberg and Matej Kristan and Jiři Matas and Aleš Leonardis and Roman Pflugfelder and Gustav Häger and Amanda Berg and Abdelrahman Eldesokey and Jörgen Ahlberg and Luka Čehovin and Tomáš Vojír and Alan Lukežič and Gustavo Fernández and Alfredo Petrosino and Alvaro Garcia-Martin and Andrés Solís Montero and Anton Varfolomieiev and Aykut Erdem and Bohyung Han and Chang-Ming Chang and Dawei Du and Erkut Erdem and Fahad Shahbaz Khan and Fatih Porikli and Fei Zhao and Filiz Bunyak and Francesco Battistone and Gao Zhu and Guna Seetharaman and Hongdong Li and Honggang Qi and Horst Bischof and Horst Possegger and Hyeonseob Nam and Jack Valmadre and Jianke Zhu and Jiayi Feng and Jochen Lang and Jose M. Martinez and Kannappan Palaniappan and Karel Lebeda and Ke Gao and Krystian Mikolajczyk and Longyin Wen and Luca Bertinetto and Mahdieh Poostchi and Mario Maresca and Martin Danelljan and Michael Arens and Ming Tang and Mooyeol Baek and Nana Fan and Noor Al-Shakarji and Ondrej Miksik and Osman Akin and Philip H. S. Torr and Qingming Huang and Rafael Martin-Nieto and Rengarajan Pelapur and Richard Bowden and Robert Laganière and Sebastian B. Krah and Shengkun Li and Shizeng Yao and Simon Hadfield and Siwei Lyu and Stefan Becker and Stuart Golodetz and Tao Hu and Thomas Mauthner and Vincenzo Santopietro and Wenbo Li and Wolfgang Hübner and Xin Li and Yang Li and Zhan Xu and Zhenyu He},
  Booktitle                = {Proceedings, European Conference on Computer Vision (ECCV) workshops},
  Year                     = {2016},
  Month                    = {8} # oct,
 Pages                    = {824--849},
  Abstract                 = {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.},
  Doi                      = {10.1007/978-3-319-48881-3_55},
  Timestamp                = {2016.11.25},
	gsid = {4263847520949387597},
%  Comment                  = {},
  Url                      = {http://dx.doi.org/10.1007/978-3-319-48881-3_55}
}
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