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Real-Time Semantic Segmentation with Label Propagation Read chapter Read first chapter

2016 | OriginalPaper | Chapter

The Thermal Infrared Visual Object Tracking VOT-TIR2016 Challenge Results

Authors : Michael Felsberg, Matej Kristan, Jiři Matas, Aleš Leonardis, Roman Pflugfelder, Gustav Häger, Amanda Berg, Abdelrahman Eldesokey, Jörgen Ahlberg, Luka Čehovin, Tomáš Vojír̃, 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

Published in: Computer Vision – ECCV 2016 Workshops

Publisher: Springer International Publishing

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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.

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previous chapter The Visual Object Tracking VOT2016 Challenge Results
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Appendix
Available only for authorised users
Footnotes
3
Here, we consider SRDCF/SRDCFir and Staple/Staple-TIR being the same, despite the fact that the TIR versions use slightly different feature vectors, see Appendices A.24 and A.13.
 
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Metadata
Title
The Thermal Infrared Visual Object Tracking VOT-TIR2016 Challenge Results
Authors
Michael Felsberg
Matej Kristan
Jiři Matas
Aleš Leonardis
Roman Pflugfelder
Gustav Häger
Amanda Berg
Abdelrahman Eldesokey
Jörgen Ahlberg
Luka Čehovin
Tomáš Vojír̃
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
Copyright Year
2016
Book
Computer Vision – ECCV 2016 Workshops

Print ISBN: 978-3-319-48880-6

Electronic ISBN: 978-3-319-48881-3

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-48881-3_55

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