The Visual Object Tracking VOT2015 Challenge Results

Matej Kristan; Jiri Matas; Ale Leonardis; Michael Felsberg; Luka Cehovin; Gustavo Fernandez; Toma Vojir; Gustav Hager; Georg Nebehay; Roman Pflugfelder; Abhinav Gupta; Adel Bibi; Alan Lukezic; Alvaro Garcia-Martin; Amir Saffari; Alfredo Petrosino; Andres Solıs Montero; Anton Varfolomieiev; Atilla Baskurt; Baojun Zhao; Bernard Ghanem; Brais Martinez; ByeongJu Lee; Bohyung Han; Chaohui Wang; Christophe Garcia; Chunyuan Zhang; Cordelia Schmid; Dacheng Tao; Daijin Kim; Dafei Huang; Danil Prokhorov; Dawei Du; Dit-Yan Yeung; Eraldo Ribeiro; Fahad Shahbaz Khan; Fatih Porikli; Filiz Bunyak; Gao Zhu; Guna Seetharaman; Hilke Kieritz; Hing Tuen Yau; Hongdong Li; Honggang Qi; Horst Bischof; Horst Possegger; Hyemin Lee; Hyeonseob Nam; Ivan Bogun; Jae-chan Jeong; Jae-il Cho; Jae-Yeong Lee; Jianke Zhu; Jianping Shi; Jiatong Li; Jiaya Jia; Jiayi Feng; Jin Gao; Jin Young Choi; Ji-Wan Kim; Jochen Lang; Jose M. Martinez; Jongwon Choi; Junliang Xing; Kai Xue; Kannappan Palaniappan; Karel Lebeda; Karteek Alahari; Ke Gao; Kimin Yun; Kin Hong Wong; Lei Luo; Liang Ma; Lipeng Ke; Longyin Wen; Luca Bertinetto; Mahdieh Pootschi; Mario Maresca; Martin Danelljan; Mei Wen; Mengdan Zhang; Michael Arens; Michel Valstar; Ming Tang; Ming-Ching Chang; Muhammad Haris Khan; Nana Fan; Naiyan Wang; Ondrej Miksik; Philip H S Torr; Qiang Wang; Rafael Martin-Nieto; Rengarajan Pelapur; Richard Bowden; Robert Laganiere; Salma Moujtahid; Sam Hare; Simon Hadfield; Siwei Lyu; Siyi Li; Song-Chun Zhu; Stefan Becker; Stefan Duffner; Stephen L Hicks; Stuart Golodetz; Sunglok Choi; Tianfu Wu; Thomas Mauthner; Tony Pridmore; Weiming Hu; Wolfgang Hubner; Xiaomeng Wang; Xin Li; Xinchu Shi; Xu Zhao; Xue Mei; Yao Shizeng; Yang Hua; Yang Li; Yang Lu; Yuezun Li; Zhaoyun Chen; Zehua Huang; Zhe Chen; Zhe Zhang; Zhenyu He; Zhibin Hong

doi:10.1109/ICCVW.2015.79

The Visual Object Tracking VOT2015 Challenge Results

Matej Kristan, Jiri Matas, Ale Leonardis, Michael Felsberg, Luka Cehovin, Gustavo Fernandez, Toma Vojir, Gustav Hager, Georg Nebehay, Roman Pflugfelder, Abhinav Gupta, Adel Bibi, Alan Lukezic, Alvaro Garcia-Martin, Amir Saffari, Alfredo Petrosino, Andres Solıs Montero, Anton Varfolomieiev, Atilla Baskurt, Baojun ZhaoBernard Ghanem, Brais Martinez, ByeongJu Lee, Bohyung Han, Chaohui Wang, Christophe Garcia, Chunyuan Zhang, Cordelia Schmid, Dacheng Tao, Daijin Kim, Dafei Huang, Danil Prokhorov, Dawei Du, Dit-Yan Yeung, Eraldo Ribeiro, Fahad Shahbaz Khan, Fatih Porikli, Filiz Bunyak, Gao Zhu, Guna Seetharaman, Hilke Kieritz, Hing Tuen Yau, Hongdong Li, Honggang Qi, Horst Bischof, Horst Possegger, Hyemin Lee, Hyeonseob Nam, Ivan Bogun, Jae-chan Jeong, Jae-il Cho, Jae-Yeong Lee, Jianke Zhu, Jianping Shi, Jiatong Li, Jiaya Jia, Jiayi Feng, Jin Gao, Jin Young Choi, Ji-Wan Kim, Jochen Lang, Jose M. Martinez, Jongwon Choi, Junliang Xing, Kai Xue, Kannappan Palaniappan, Karel Lebeda, Karteek Alahari, Ke Gao, Kimin Yun, Kin Hong Wong, Lei Luo, Liang Ma, Lipeng Ke, Longyin Wen, Luca Bertinetto, Mahdieh Pootschi, Mario Maresca, Martin Danelljan, Mei Wen, Mengdan Zhang, Michael Arens, Michel Valstar, Ming Tang, Ming-Ching Chang, Muhammad Haris Khan, Nana Fan, Naiyan Wang, Ondrej Miksik, Philip H S Torr, Qiang Wang, Rafael Martin-Nieto, Rengarajan Pelapur, Richard Bowden, Robert Laganiere, Salma Moujtahid, Sam Hare, Simon Hadfield, Siwei Lyu, Siyi Li, Song-Chun Zhu, Stefan Becker, Stefan Duffner, Stephen L Hicks, Stuart Golodetz, Sunglok Choi, Tianfu Wu, Thomas Mauthner, Tony Pridmore, Weiming Hu, Wolfgang Hubner, Xiaomeng Wang, Xin Li, Xinchu Shi, Xu Zhao, Xue Mei, Yao Shizeng, Yang Hua, Yang Li, Yang Lu, Yuezun Li, Zhaoyun Chen, Zehua Huang, Zhe Chen, Zhe Zhang, Zhenyu He, Zhibin Hong

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

281 Scopus citations

Abstract

The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 62 trackers are presented. The number of tested trackers makes VOT 2015 the largest benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the appendix. Features of the VOT2015 challenge that go beyond its VOT2014 predecessor are: (i) a new VOT2015 dataset twice as large as in VOT2014 with full annotation of targets by rotated bounding boxes and per-frame attribute, (ii) extensions of the VOT2014 evaluation methodology by introduction of a new performance measure. 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	2015 IEEE International Conference on Computer Vision Workshop (ICCVW)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	564-586
Number of pages	23
ISBN (Print)	9781467397117
DOIs	https://doi.org/10.1109/ICCVW.2015.79
State	Published - Feb 16 2016

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10.1109/ICCVW.2015.79

https://repository.kaust.edu.sa/bitstream/10754/605657/1/Kristan_The_Visual_Object_ICCV_2015_paper.pdf

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Kristan, M., Matas, J., Leonardis, A., Felsberg, M., Cehovin, L., Fernandez, G., Vojir, T., Hager, G., Nebehay, G., Pflugfelder, R., Gupta, A., Bibi, A., Lukezic, A., Garcia-Martin, A., Saffari, A., Petrosino, A., Montero, A. S., Varfolomieiev, A., Baskurt, A., ... Hong, Z. (2016). The Visual Object Tracking VOT2015 Challenge Results. In 2015 IEEE International Conference on Computer Vision Workshop (ICCVW) (pp. 564-586). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICCVW.2015.79

@inproceedings{ebc6db7e4f0f41568f68411b7b4b4aa6,

title = "The Visual Object Tracking VOT2015 Challenge Results",

abstract = "The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 62 trackers are presented. The number of tested trackers makes VOT 2015 the largest benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the appendix. Features of the VOT2015 challenge that go beyond its VOT2014 predecessor are: (i) a new VOT2015 dataset twice as large as in VOT2014 with full annotation of targets by rotated bounding boxes and per-frame attribute, (ii) extensions of the VOT2014 evaluation methodology by introduction of a new performance measure. The dataset, the evaluation kit as well as the results are publicly available at the challenge website.",

author = "Matej Kristan and Jiri Matas and Ale Leonardis and Michael Felsberg and Luka Cehovin and Gustavo Fernandez and Toma Vojir and Gustav Hager and Georg Nebehay and Roman Pflugfelder and Abhinav Gupta and Adel Bibi and Alan Lukezic and Alvaro Garcia-Martin and Amir Saffari and Alfredo Petrosino and Montero, {Andres Solıs} and Anton Varfolomieiev and Atilla Baskurt and Baojun Zhao and Bernard Ghanem and Brais Martinez and ByeongJu Lee and Bohyung Han and Chaohui Wang and Christophe Garcia and Chunyuan Zhang and Cordelia Schmid and Dacheng Tao and Daijin Kim and Dafei Huang and Danil Prokhorov and Dawei Du and Dit-Yan Yeung and Eraldo Ribeiro and Khan, {Fahad Shahbaz} and Fatih Porikli and Filiz Bunyak and Gao Zhu and Guna Seetharaman and Hilke Kieritz and Yau, {Hing Tuen} and Hongdong Li and Honggang Qi and Horst Bischof and Horst Possegger and Hyemin Lee and Hyeonseob Nam and Ivan Bogun and Jae-chan Jeong and Jae-il Cho and Jae-Yeong Lee and Jianke Zhu and Jianping Shi and Jiatong Li and Jiaya Jia and Jiayi Feng and Jin Gao and Choi, {Jin Young} and Ji-Wan Kim and Jochen Lang and Martinez, {Jose M.} and Jongwon Choi and Junliang Xing and Kai Xue and Kannappan Palaniappan and Karel Lebeda and Karteek Alahari and Ke Gao and Kimin Yun and Wong, {Kin Hong} and Lei Luo and Liang Ma and Lipeng Ke and Longyin Wen and Luca Bertinetto and Mahdieh Pootschi and Mario Maresca and Martin Danelljan and Mei Wen and Mengdan Zhang and Michael Arens and Michel Valstar and Ming Tang and Ming-Ching Chang and Khan, {Muhammad Haris} and Nana Fan and Naiyan Wang and Ondrej Miksik and Torr, {Philip H S} and Qiang Wang and Rafael Martin-Nieto and Rengarajan Pelapur and Richard Bowden and Robert Laganiere and Salma Moujtahid and Sam Hare and Simon Hadfield and Siwei Lyu and Siyi Li and Song-Chun Zhu and Stefan Becker and Stefan Duffner and Hicks, {Stephen L} and Stuart Golodetz and Sunglok Choi and Tianfu Wu and Thomas Mauthner and Tony Pridmore and Weiming Hu and Wolfgang Hubner and Xiaomeng Wang and Xin Li and Xinchu Shi and Xu Zhao and Xue Mei and Yao Shizeng and Yang Hua and Yang Li and Yang Lu and Yuezun Li and Zhaoyun Chen and Zehua Huang and Zhe Chen and Zhe Zhang and Zhenyu He and Zhibin Hong",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: 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 seventh framework programme under grant agreement no 257906. Jiri Matas and Tomas 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). Michael Felsberg and Gustav H¨ager were supported by the Swedish Foundation for Strategic Research through the project CUAS and the Swedish Research Council trough the project EMC2. Some experiments where run on GPUs donated by NVIDIA.",

year = "2016",

month = feb,

day = "16",

doi = "10.1109/ICCVW.2015.79",

language = "English (US)",

isbn = "9781467397117",

pages = "564--586",

booktitle = "2015 IEEE International Conference on Computer Vision Workshop (ICCVW)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

}

Kristan, M, Matas, J, Leonardis, A, Felsberg, M, Cehovin, L, Fernandez, G, Vojir, T, Hager, G, Nebehay, G, Pflugfelder, R, Gupta, A, Bibi, A, Lukezic, A, Garcia-Martin, A, Saffari, A, Petrosino, A, Montero, AS, Varfolomieiev, A, Baskurt, A, Zhao, B, Ghanem, B, Martinez, B, Lee, B, Han, B, Wang, C, Garcia, C, Zhang, C, Schmid, C, Tao, D, Kim, D, Huang, D, Prokhorov, D, Du, D, Yeung, D-Y, Ribeiro, E, Khan, FS, Porikli, F, Bunyak, F, Zhu, G, Seetharaman, G, Kieritz, H, Yau, HT, Li, H, Qi, H, Bischof, H, Possegger, H, Lee, H, Nam, H, Bogun, I, Jeong, J, Cho, J, Lee, J-Y, Zhu, J, Shi, J, Li, J, Jia, J, Feng, J, Gao, J, Choi, JY, Kim, J-W, Lang, J, Martinez, JM, Choi, J, Xing, J, Xue, K, Palaniappan, K, Lebeda, K, Alahari, K, Gao, K, Yun, K, Wong, KH, Luo, L, Ma, L, Ke, L, Wen, L, Bertinetto, L, Pootschi, M, Maresca, M, Danelljan, M, Wen, M, Zhang, M, Arens, M, Valstar, M, Tang, M, Chang, M-C, Khan, MH, Fan, N, Wang, N, Miksik, O, Torr, PHS, Wang, Q, Martin-Nieto, R, Pelapur, R, Bowden, R, Laganiere, R, Moujtahid, S, Hare, S, Hadfield, S, Lyu, S, Li, S, Zhu, S-C, Becker, S, Duffner, S, Hicks, SL, Golodetz, S, Choi, S, Wu, T, Mauthner, T, Pridmore, T, Hu, W, Hubner, W, Wang, X, Li, X, Shi, X, Zhao, X, Mei, X, Shizeng, Y, Hua, Y, Li, Y, Lu, Y, Li, Y, Chen, Z, Huang, Z, Chen, Z, Zhang, Z, He, Z & Hong, Z 2016, The Visual Object Tracking VOT2015 Challenge Results. in 2015 IEEE International Conference on Computer Vision Workshop (ICCVW). Institute of Electrical and Electronics Engineers (IEEE), pp. 564-586. https://doi.org/10.1109/ICCVW.2015.79

TY - GEN

T1 - The Visual Object Tracking VOT2015 Challenge Results

AU - Kristan, Matej

AU - Matas, Jiri

AU - Leonardis, Ale

AU - Felsberg, Michael

AU - Cehovin, Luka

AU - Fernandez, Gustavo

AU - Vojir, Toma

AU - Hager, Gustav

AU - Nebehay, Georg

AU - Pflugfelder, Roman

AU - Gupta, Abhinav

AU - Bibi, Adel

AU - Lukezic, Alan

AU - Garcia-Martin, Alvaro

AU - Saffari, Amir

AU - Petrosino, Alfredo

AU - Montero, Andres Solıs

AU - Varfolomieiev, Anton

AU - Baskurt, Atilla

AU - Zhao, Baojun

AU - Ghanem, Bernard

AU - Martinez, Brais

AU - Lee, ByeongJu

AU - Han, Bohyung

AU - Wang, Chaohui

AU - Garcia, Christophe

AU - Zhang, Chunyuan

AU - Schmid, Cordelia

AU - Tao, Dacheng

AU - Kim, Daijin

AU - Huang, Dafei

AU - Prokhorov, Danil

AU - Du, Dawei

AU - Yeung, Dit-Yan

AU - Ribeiro, Eraldo

AU - Khan, Fahad Shahbaz

AU - Porikli, Fatih

AU - Bunyak, Filiz

AU - Zhu, Gao

AU - Seetharaman, Guna

AU - Kieritz, Hilke

AU - Yau, Hing Tuen

AU - Li, Hongdong

AU - Qi, Honggang

AU - Bischof, Horst

AU - Possegger, Horst

AU - Lee, Hyemin

AU - Nam, Hyeonseob

AU - Bogun, Ivan

AU - Jeong, Jae-chan

AU - Cho, Jae-il

AU - Lee, Jae-Yeong

AU - Zhu, Jianke

AU - Shi, Jianping

AU - Li, Jiatong

AU - Jia, Jiaya

AU - Feng, Jiayi

AU - Gao, Jin

AU - Choi, Jin Young

AU - Kim, Ji-Wan

AU - Lang, Jochen

AU - Martinez, Jose M.

AU - Choi, Jongwon

AU - Xing, Junliang

AU - Xue, Kai

AU - Palaniappan, Kannappan

AU - Lebeda, Karel

AU - Alahari, Karteek

AU - Gao, Ke

AU - Yun, Kimin

AU - Wong, Kin Hong

AU - Luo, Lei

AU - Ma, Liang

AU - Ke, Lipeng

AU - Wen, Longyin

AU - Bertinetto, Luca

AU - Pootschi, Mahdieh

AU - Maresca, Mario

AU - Danelljan, Martin

AU - Wen, Mei

AU - Zhang, Mengdan

AU - Arens, Michael

AU - Valstar, Michel

AU - Tang, Ming

AU - Chang, Ming-Ching

AU - Khan, Muhammad Haris

AU - Fan, Nana

AU - Wang, Naiyan

AU - Miksik, Ondrej

AU - Torr, Philip H S

AU - Wang, Qiang

AU - Martin-Nieto, Rafael

AU - Pelapur, Rengarajan

AU - Bowden, Richard

AU - Laganiere, Robert

AU - Moujtahid, Salma

AU - Hare, Sam

AU - Hadfield, Simon

AU - Lyu, Siwei

AU - Li, Siyi

AU - Zhu, Song-Chun

AU - Becker, Stefan

AU - Duffner, Stefan

AU - Hicks, Stephen L

AU - Golodetz, Stuart

AU - Choi, Sunglok

AU - Wu, Tianfu

AU - Mauthner, Thomas

AU - Pridmore, Tony

AU - Hu, Weiming

AU - Hubner, Wolfgang

AU - Wang, Xiaomeng

AU - Li, Xin

AU - Shi, Xinchu

AU - Zhao, Xu

AU - Mei, Xue

AU - Shizeng, Yao

AU - Hua, Yang

AU - Li, Yang

AU - Lu, Yang

AU - Li, Yuezun

AU - Chen, Zhaoyun

AU - Huang, Zehua

AU - Chen, Zhe

AU - Zhang, Zhe

AU - He, Zhenyu

AU - Hong, Zhibin

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: 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 seventh framework programme under grant agreement no 257906. Jiri Matas and Tomas 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). Michael Felsberg and Gustav H¨ager were supported by the Swedish Foundation for Strategic Research through the project CUAS and the Swedish Research Council trough the project EMC2. Some experiments where run on GPUs donated by NVIDIA.

PY - 2016/2/16

Y1 - 2016/2/16

N2 - The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 62 trackers are presented. The number of tested trackers makes VOT 2015 the largest benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the appendix. Features of the VOT2015 challenge that go beyond its VOT2014 predecessor are: (i) a new VOT2015 dataset twice as large as in VOT2014 with full annotation of targets by rotated bounding boxes and per-frame attribute, (ii) extensions of the VOT2014 evaluation methodology by introduction of a new performance measure. The dataset, the evaluation kit as well as the results are publicly available at the challenge website.

AB - The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 62 trackers are presented. The number of tested trackers makes VOT 2015 the largest benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the appendix. Features of the VOT2015 challenge that go beyond its VOT2014 predecessor are: (i) a new VOT2015 dataset twice as large as in VOT2014 with full annotation of targets by rotated bounding boxes and per-frame attribute, (ii) extensions of the VOT2014 evaluation methodology by introduction of a new performance measure. The dataset, the evaluation kit as well as the results are publicly available at the challenge website.

UR - http://hdl.handle.net/10754/605657

UR - http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7406428

UR - http://www.scopus.com/inward/record.url?scp=84962023046&partnerID=8YFLogxK

U2 - 10.1109/ICCVW.2015.79

DO - 10.1109/ICCVW.2015.79

M3 - Conference contribution

SN - 9781467397117

SP - 564

EP - 586

BT - 2015 IEEE International Conference on Computer Vision Workshop (ICCVW)

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

The Visual Object Tracking VOT2015 Challenge Results

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