The Visual Object Tracking VOT2017 Challenge Results

Matej Kristan, Aleš Leonardis, Jiri Matas, Michael Felsberg, Roman Pflugfelder, Luka Čehovin Zajc, Tomáš Vojír, Gustav Häger, Alan Lukežič, Abdelrahman Eldesokey, Gustavo Fernández, Álvaro García-Martín, A. Muhic, Alfredo Petrosino, Alireza Memarmoghadam, Andrea Vedaldi, Antoine Manzanera, Antoine Tran, Aydin Alatan, Bogdan MocanuBoyu Chen, Chang Huang, Changsheng Xu, Chong Sun, Dalong Du, David Zhang, Dawei Du, Deepak Mishra, Erhan Gundogdu, Erik Velasco-Salido, Fahad Shahbaz Khan, Francesco Battistone, Gorthi R.K.Sai Subrahmanyam, Goutam Bhat, Guan Huang, Guilherme Bastos, Guna Seetharaman, Hongliang Zhang, Houqiang Li, Huchuan Lu, Isabela Drummond, Jack Valmadre, Jae Chan Jeong, Jae Il Cho, Jae Yeong Lee, Jana Noskova, Jianke Zhu, Jin Gao, Jingyu Liu, Ji Wan Kim, João F. Henriques, José M. Martínez, Junfei Zhuang, Junliang Xing, Junyu Gao, Kai Chen, Kannappan Palaniappan, Karel Lebeda, Ke Gao, Kris M. Kitani, Lei Zhang, Lijun Wang, Lingxiao Yang, Longyin Wen, Luca Bertinetto, Mahdieh Poostchi, Martin Danelljan, Matthias Mueller, Mengdan Zhang, Ming Hsuan Yang, Nianhao Xie, Ning Wang, Ondrej Miksik, P. Moallem, M. Pallavi Venugopal, Pedro Senna, Philip H.S. Torr, Qiang Wang, Qifeng Yu, Qingming Huang, Rafael Martín-Nieto, Richard Bowden, Risheng Liu, Ruxandra Tapu, Simon Hadfield, Siwei Lyu, Stuart Golodetz, Sunglok Choi, Tianzhu Zhang, Titus Zaharia, Vincenzo Santopietro, Wei Zou, Weiming Hu, Wenbing Tao, Wenbo Li, Wengang Zhou, Xianguo Yu, Xiao Bian, Yang Li, Yifan Xing, Yingruo Fan, Zheng Zhu, Zhipeng Zhang, Zhiqun He

Research output: Chapter in Book/Report/Conference proceedingConference contribution

126 Citations (Scopus)

Abstract

The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative. Results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years. The evaluation included the standard VOT and other popular methodologies and a new 'real-time' experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The VOT2017 goes beyond its predecessors by (i) improving the VOT public dataset and introducing a separate VOT2017 sequestered dataset, (ii) introducing a realtime tracking experiment and (iii) releasing a redesigned toolkit that supports complex experiments. The dataset, the evaluation kit and the results are publicly available at the challenge website1.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1949-1972
Number of pages24
ISBN (Electronic)9781538610343
DOIs
Publication statusPublished - 2017 Jul 1
Event16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017 - Venice, Italy
Duration: 2017 Oct 222017 Oct 29

Publication series

NameProceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
Volume2018-January

Other

Other16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017
CountryItaly
CityVenice
Period17/10/2217/10/29

Fingerprint

Experiments
Benchmarking
Computer vision
Sensors

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

Cite this

Kristan, M., Leonardis, A., Matas, J., Felsberg, M., Pflugfelder, R., Zajc, L. Č., ... He, Z. (2017). The Visual Object Tracking VOT2017 Challenge Results. In Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017 (pp. 1949-1972). (Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCVW.2017.230
Kristan, Matej ; Leonardis, Aleš ; Matas, Jiri ; Felsberg, Michael ; Pflugfelder, Roman ; Zajc, Luka Čehovin ; Vojír, Tomáš ; Häger, Gustav ; Lukežič, Alan ; Eldesokey, Abdelrahman ; Fernández, Gustavo ; García-Martín, Álvaro ; Muhic, A. ; Petrosino, Alfredo ; Memarmoghadam, Alireza ; Vedaldi, Andrea ; Manzanera, Antoine ; Tran, Antoine ; Alatan, Aydin ; Mocanu, Bogdan ; Chen, Boyu ; Huang, Chang ; Xu, Changsheng ; Sun, Chong ; Du, Dalong ; Zhang, David ; Du, Dawei ; Mishra, Deepak ; Gundogdu, Erhan ; Velasco-Salido, Erik ; Khan, Fahad Shahbaz ; Battistone, Francesco ; Subrahmanyam, Gorthi R.K.Sai ; Bhat, Goutam ; Huang, Guan ; Bastos, Guilherme ; Seetharaman, Guna ; Zhang, Hongliang ; Li, Houqiang ; Lu, Huchuan ; Drummond, Isabela ; Valmadre, Jack ; Jeong, Jae Chan ; Cho, Jae Il ; Lee, Jae Yeong ; Noskova, Jana ; Zhu, Jianke ; Gao, Jin ; Liu, Jingyu ; Kim, Ji Wan ; Henriques, João F. ; Martínez, José M. ; Zhuang, Junfei ; Xing, Junliang ; Gao, Junyu ; Chen, Kai ; Palaniappan, Kannappan ; Lebeda, Karel ; Gao, Ke ; Kitani, Kris M. ; Zhang, Lei ; Wang, Lijun ; Yang, Lingxiao ; Wen, Longyin ; Bertinetto, Luca ; Poostchi, Mahdieh ; Danelljan, Martin ; Mueller, Matthias ; Zhang, Mengdan ; Yang, Ming Hsuan ; Xie, Nianhao ; Wang, Ning ; Miksik, Ondrej ; Moallem, P. ; Pallavi Venugopal, M. ; Senna, Pedro ; Torr, Philip H.S. ; Wang, Qiang ; Yu, Qifeng ; Huang, Qingming ; Martín-Nieto, Rafael ; Bowden, Richard ; Liu, Risheng ; Tapu, Ruxandra ; Hadfield, Simon ; Lyu, Siwei ; Golodetz, Stuart ; Choi, Sunglok ; Zhang, Tianzhu ; Zaharia, Titus ; Santopietro, Vincenzo ; Zou, Wei ; Hu, Weiming ; Tao, Wenbing ; Li, Wenbo ; Zhou, Wengang ; Yu, Xianguo ; Bian, Xiao ; Li, Yang ; Xing, Yifan ; Fan, Yingruo ; Zhu, Zheng ; Zhang, Zhipeng ; He, Zhiqun. / The Visual Object Tracking VOT2017 Challenge Results. Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1949-1972 (Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017).
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abstract = "The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative. Results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years. The evaluation included the standard VOT and other popular methodologies and a new 'real-time' experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The VOT2017 goes beyond its predecessors by (i) improving the VOT public dataset and introducing a separate VOT2017 sequestered dataset, (ii) introducing a realtime tracking experiment and (iii) releasing a redesigned toolkit that supports complex experiments. The dataset, the evaluation kit and the results are publicly available at the challenge website1.",
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Kristan, M, Leonardis, A, Matas, J, Felsberg, M, Pflugfelder, R, Zajc, LČ, Vojír, T, Häger, G, Lukežič, A, Eldesokey, A, Fernández, G, García-Martín, Á, Muhic, A, Petrosino, A, Memarmoghadam, A, Vedaldi, A, Manzanera, A, Tran, A, Alatan, A, Mocanu, B, Chen, B, Huang, C, Xu, C, Sun, C, Du, D, Zhang, D, Du, D, Mishra, D, Gundogdu, E, Velasco-Salido, E, Khan, FS, Battistone, F, Subrahmanyam, GRKS, Bhat, G, Huang, G, Bastos, G, Seetharaman, G, Zhang, H, Li, H, Lu, H, Drummond, I, Valmadre, J, Jeong, JC, Cho, JI, Lee, JY, Noskova, J, Zhu, J, Gao, J, Liu, J, Kim, JW, Henriques, JF, Martínez, JM, Zhuang, J, Xing, J, Gao, J, Chen, K, Palaniappan, K, Lebeda, K, Gao, K, Kitani, KM, Zhang, L, Wang, L, Yang, L, Wen, L, Bertinetto, L, Poostchi, M, Danelljan, M, Mueller, M, Zhang, M, Yang, MH, Xie, N, Wang, N, Miksik, O, Moallem, P, Pallavi Venugopal, M, Senna, P, Torr, PHS, Wang, Q, Yu, Q, Huang, Q, Martín-Nieto, R, Bowden, R, Liu, R, Tapu, R, Hadfield, S, Lyu, S, Golodetz, S, Choi, S, Zhang, T, Zaharia, T, Santopietro, V, Zou, W, Hu, W, Tao, W, Li, W, Zhou, W, Yu, X, Bian, X, Li, Y, Xing, Y, Fan, Y, Zhu, Z, Zhang, Z & He, Z 2017, The Visual Object Tracking VOT2017 Challenge Results. in Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017. Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1949-1972, 16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017, Venice, Italy, 17/10/22. https://doi.org/10.1109/ICCVW.2017.230

The Visual Object Tracking VOT2017 Challenge Results. / Kristan, Matej; Leonardis, Aleš; Matas, Jiri; Felsberg, Michael; Pflugfelder, Roman; Zajc, Luka Čehovin; Vojír, Tomáš; Häger, Gustav; Lukežič, Alan; Eldesokey, Abdelrahman; Fernández, Gustavo; García-Martín, Álvaro; Muhic, A.; Petrosino, Alfredo; Memarmoghadam, Alireza; Vedaldi, Andrea; Manzanera, Antoine; Tran, Antoine; Alatan, Aydin; Mocanu, Bogdan; Chen, Boyu; Huang, Chang; Xu, Changsheng; Sun, Chong; Du, Dalong; Zhang, David; Du, Dawei; Mishra, Deepak; Gundogdu, Erhan; Velasco-Salido, Erik; Khan, Fahad Shahbaz; Battistone, Francesco; Subrahmanyam, Gorthi R.K.Sai; Bhat, Goutam; Huang, Guan; Bastos, Guilherme; Seetharaman, Guna; Zhang, Hongliang; Li, Houqiang; Lu, Huchuan; Drummond, Isabela; Valmadre, Jack; Jeong, Jae Chan; Cho, Jae Il; Lee, Jae Yeong; Noskova, Jana; Zhu, Jianke; Gao, Jin; Liu, Jingyu; Kim, Ji Wan; Henriques, João F.; Martínez, José M.; Zhuang, Junfei; Xing, Junliang; Gao, Junyu; Chen, Kai; Palaniappan, Kannappan; Lebeda, Karel; Gao, Ke; Kitani, Kris M.; Zhang, Lei; Wang, Lijun; Yang, Lingxiao; Wen, Longyin; Bertinetto, Luca; Poostchi, Mahdieh; Danelljan, Martin; Mueller, Matthias; Zhang, Mengdan; Yang, Ming Hsuan; Xie, Nianhao; Wang, Ning; Miksik, Ondrej; Moallem, P.; Pallavi Venugopal, M.; Senna, Pedro; Torr, Philip H.S.; Wang, Qiang; Yu, Qifeng; Huang, Qingming; Martín-Nieto, Rafael; Bowden, Richard; Liu, Risheng; Tapu, Ruxandra; Hadfield, Simon; Lyu, Siwei; Golodetz, Stuart; Choi, Sunglok; Zhang, Tianzhu; Zaharia, Titus; Santopietro, Vincenzo; Zou, Wei; Hu, Weiming; Tao, Wenbing; Li, Wenbo; Zhou, Wengang; Yu, Xianguo; Bian, Xiao; Li, Yang; Xing, Yifan; Fan, Yingruo; Zhu, Zheng; Zhang, Zhipeng; He, Zhiqun.

Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1949-1972 (Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - The Visual Object Tracking VOT2017 Challenge Results

AU - Kristan, Matej

AU - Leonardis, Aleš

AU - Matas, Jiri

AU - Felsberg, Michael

AU - Pflugfelder, Roman

AU - Zajc, Luka Čehovin

AU - Vojír, Tomáš

AU - Häger, Gustav

AU - Lukežič, Alan

AU - Eldesokey, Abdelrahman

AU - Fernández, Gustavo

AU - García-Martín, Álvaro

AU - Muhic, A.

AU - Petrosino, Alfredo

AU - Memarmoghadam, Alireza

AU - Vedaldi, Andrea

AU - Manzanera, Antoine

AU - Tran, Antoine

AU - Alatan, Aydin

AU - Mocanu, Bogdan

AU - Chen, Boyu

AU - Huang, Chang

AU - Xu, Changsheng

AU - Sun, Chong

AU - Du, Dalong

AU - Zhang, David

AU - Du, Dawei

AU - Mishra, Deepak

AU - Gundogdu, Erhan

AU - Velasco-Salido, Erik

AU - Khan, Fahad Shahbaz

AU - Battistone, Francesco

AU - Subrahmanyam, Gorthi R.K.Sai

AU - Bhat, Goutam

AU - Huang, Guan

AU - Bastos, Guilherme

AU - Seetharaman, Guna

AU - Zhang, Hongliang

AU - Li, Houqiang

AU - Lu, Huchuan

AU - Drummond, Isabela

AU - Valmadre, Jack

AU - Jeong, Jae Chan

AU - Cho, Jae Il

AU - Lee, Jae Yeong

AU - Noskova, Jana

AU - Zhu, Jianke

AU - Gao, Jin

AU - Liu, Jingyu

AU - Kim, Ji Wan

AU - Henriques, João F.

AU - Martínez, José M.

AU - Zhuang, Junfei

AU - Xing, Junliang

AU - Gao, Junyu

AU - Chen, Kai

AU - Palaniappan, Kannappan

AU - Lebeda, Karel

AU - Gao, Ke

AU - Kitani, Kris M.

AU - Zhang, Lei

AU - Wang, Lijun

AU - Yang, Lingxiao

AU - Wen, Longyin

AU - Bertinetto, Luca

AU - Poostchi, Mahdieh

AU - Danelljan, Martin

AU - Mueller, Matthias

AU - Zhang, Mengdan

AU - Yang, Ming Hsuan

AU - Xie, Nianhao

AU - Wang, Ning

AU - Miksik, Ondrej

AU - Moallem, P.

AU - Pallavi Venugopal, M.

AU - Senna, Pedro

AU - Torr, Philip H.S.

AU - Wang, Qiang

AU - Yu, Qifeng

AU - Huang, Qingming

AU - Martín-Nieto, Rafael

AU - Bowden, Richard

AU - Liu, Risheng

AU - Tapu, Ruxandra

AU - Hadfield, Simon

AU - Lyu, Siwei

AU - Golodetz, Stuart

AU - Choi, Sunglok

AU - Zhang, Tianzhu

AU - Zaharia, Titus

AU - Santopietro, Vincenzo

AU - Zou, Wei

AU - Hu, Weiming

AU - Tao, Wenbing

AU - Li, Wenbo

AU - Zhou, Wengang

AU - Yu, Xianguo

AU - Bian, Xiao

AU - Li, Yang

AU - Xing, Yifan

AU - Fan, Yingruo

AU - Zhu, Zheng

AU - Zhang, Zhipeng

AU - He, Zhiqun

PY - 2017/7/1

Y1 - 2017/7/1

N2 - The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative. Results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years. The evaluation included the standard VOT and other popular methodologies and a new 'real-time' experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The VOT2017 goes beyond its predecessors by (i) improving the VOT public dataset and introducing a separate VOT2017 sequestered dataset, (ii) introducing a realtime tracking experiment and (iii) releasing a redesigned toolkit that supports complex experiments. The dataset, the evaluation kit and the results are publicly available at the challenge website1.

AB - The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative. Results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years. The evaluation included the standard VOT and other popular methodologies and a new 'real-time' experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The VOT2017 goes beyond its predecessors by (i) improving the VOT public dataset and introducing a separate VOT2017 sequestered dataset, (ii) introducing a realtime tracking experiment and (iii) releasing a redesigned toolkit that supports complex experiments. The dataset, the evaluation kit and the results are publicly available at the challenge website1.

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U2 - 10.1109/ICCVW.2017.230

DO - 10.1109/ICCVW.2017.230

M3 - Conference contribution

AN - SCOPUS:85046256196

T3 - Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017

SP - 1949

EP - 1972

BT - Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Kristan M, Leonardis A, Matas J, Felsberg M, Pflugfelder R, Zajc LČ et al. The Visual Object Tracking VOT2017 Challenge Results. In Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1949-1972. (Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017). https://doi.org/10.1109/ICCVW.2017.230