The sixth visual object tracking VOT2018 challenge results

Matej Kristan; Aleš Leonardis; Jiří Matas; Michael Felsberg; Roman Pflugfelder; Luka Čehovin Zajc; Tomáš Vojír̃; Goutam Bhat; Alan Lukežič; Abdelrahman Eldesokey; Gustavo Fernández; Álvaro García-Martín; Álvaro Iglesias-Arias; A. Aydin Alatan; Abel González-García; Alfredo Petrosino; Alireza Memarmoghadam; Andrea Vedaldi; Andrej Muhič; Anfeng He; Arnold Smeulders; Asanka G. Perera; Bo Li; Boyu Chen; Changick Kim; Changsheng Xu; Changzhen Xiong; Cheng Tian; Chong Luo; Chong Sun; Cong Hao; Daijin Kim; Deepak Mishra; Deming Chen; Dong Wang; Dongyoon Wee; Efstratios Gavves; Erhan Gundogdu; Erik Velasco-Salido; Fahad Shahbaz Khan; Fan Yang; Fei Zhao; Feng Li; Francesco Battistone; George De Ath; Jing Li; Ning Wang; Ran Tao; Tianzhu Zhang; Yan Li

doi:10.1007/978-3-030-11009-3_1

The sixth visual object tracking VOT2018 challenge results

Matej Kristan^*, Aleš Leonardis, Jiří Matas, Michael Felsberg, Roman Pflugfelder, Luka Čehovin Zajc, Tomáš Vojír̃, Goutam Bhat, Alan Lukežič, Abdelrahman Eldesokey, Gustavo Fernández, Álvaro García-Martín, Álvaro Iglesias-Arias, A. Aydin Alatan, Abel González-García, Alfredo Petrosino, Alireza Memarmoghadam, Andrea Vedaldi, Andrej Muhič, Anfeng HeArnold Smeulders, Asanka G. Perera, Bo Li, Boyu Chen, Changick Kim, Changsheng Xu, Changzhen Xiong, Cheng Tian, Chong Luo, Chong Sun, Cong Hao, Daijin Kim, Deepak Mishra, Deming Chen, Dong Wang, Dongyoon Wee, Efstratios Gavves, Erhan Gundogdu, Erik Velasco-Salido, Fahad Shahbaz Khan, Fan Yang, Fei Zhao, Feng Li, Francesco Battistone, George De Ath, Jing Li, Ning Wang, Ran Tao, Tianzhu Zhang, Yan Li

^*Corresponding author for this work

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

201 Scopus citations

Abstract

The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis and a “real-time” experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. A long-term tracking subchallenge has been introduced to the set of standard VOT sub-challenges. The new subchallenge focuses on long-term tracking properties, namely coping with target disappearance and reappearance. A new dataset has been compiled and a performance evaluation methodology that focuses on long-term tracking capabilities has been adopted. The VOT toolkit has been updated to support both standard short-term and the new long-term tracking subchallenges. 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 dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net).

Original language	English (US)
Title of host publication	Computer Vision – ECCV 2018 Workshops, Proceedings
Editors	Laura Leal-Taixé, Stefan Roth
Publisher	Springer Verlag
Pages	3-53
Number of pages	51
ISBN (Print)	9783030110086
DOIs	https://doi.org/10.1007/978-3-030-11009-3_1
State	Published - 2019
Event	15th European Conference on Computer Vision, ECCV 2018 - Munich, Germany Duration: Sep 8 2018 → Sep 14 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11129 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	15th European Conference on Computer Vision, ECCV 2018
Country/Territory	Germany
City	Munich
Period	09/8/18 → 09/14/18

Bibliographical note

Funding Information:
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 project J2-8175. Jiˇri Matas and Tomáˇs Vojí˜r were supported by the Czech Science Foundation Project GACR P103/12/G084. Michael Felsberg and Gustav Häger were supported by WASP, VR (EMC2), SSF (SymbiCloud), and SNIC. Roman Pflugfelder and Gustavo Fernández were supported by the AIT Strategic Research Programme 2017 Visual Surveillance and Insight. The challenge was sponsored by Faculty of Computer Science, University of Ljubljana, Slovenia.

Publisher Copyright:
© Springer Nature Switzerland AG 2019.

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-11009-3_1

Cite this

Kristan, M., Leonardis, A., Matas, J., Felsberg, M., Pflugfelder, R., Zajc, L. Č., Vojír̃, T., Bhat, G., Lukežič, A., Eldesokey, A., Fernández, G., García-Martín, Á., Iglesias-Arias, Á., Alatan, A. A., González-García, A., Petrosino, A., Memarmoghadam, A., Vedaldi, A., Muhič, A., ... Li, Y. (2019). The sixth visual object tracking VOT2018 challenge results. In L. Leal-Taixé, & S. Roth (Eds.), Computer Vision – ECCV 2018 Workshops, Proceedings (pp. 3-53). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11129 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-11009-3_1

Kristan, Matej ; Leonardis, Aleš ; Matas, Jiří et al. / The sixth visual object tracking VOT2018 challenge results. Computer Vision – ECCV 2018 Workshops, Proceedings. editor / Laura Leal-Taixé ; Stefan Roth. Springer Verlag, 2019. pp. 3-53 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{fd8eff7c2a3c4248bf204c630263d335,

title = "The sixth visual object tracking VOT2018 challenge results",

abstract = "The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis and a “real-time” experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. A long-term tracking subchallenge has been introduced to the set of standard VOT sub-challenges. The new subchallenge focuses on long-term tracking properties, namely coping with target disappearance and reappearance. A new dataset has been compiled and a performance evaluation methodology that focuses on long-term tracking capabilities has been adopted. The VOT toolkit has been updated to support both standard short-term and the new long-term tracking subchallenges. 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 dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net).",

author = "Matej Kristan and Ale{\v s} Leonardis and Ji{\v r}{\'i} Matas and Michael Felsberg and Roman Pflugfelder and Zajc, {Luka {\v C}ehovin} and Tom{\'a}{\v s} Voj{\'i}{\~r} and Goutam Bhat and Alan Luke{\v z}i{\v c} and Abdelrahman Eldesokey and Gustavo Fern{\'a}ndez and {\'A}lvaro Garc{\'i}a-Mart{\'i}n and {\'A}lvaro Iglesias-Arias and Alatan, {A. Aydin} and Abel Gonz{\'a}lez-Garc{\'i}a and Alfredo Petrosino and Alireza Memarmoghadam and Andrea Vedaldi and Andrej Muhi{\v c} and Anfeng He and Arnold Smeulders and Perera, {Asanka G.} and Bo Li and Boyu Chen and Changick Kim and Changsheng Xu and Changzhen Xiong and Cheng Tian and Chong Luo and Chong Sun and Cong Hao and Daijin Kim and Deepak Mishra and Deming Chen and Dong Wang and Dongyoon Wee and Efstratios Gavves and Erhan Gundogdu and Erik Velasco-Salido and Khan, {Fahad Shahbaz} and Fan Yang and Fei Zhao and Feng Li and Francesco Battistone and {De Ath}, George and Jing Li and Ning Wang and Ran Tao and Tianzhu Zhang and Yan Li",

note = "Funding Information: 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 project J2-8175. Jiˇri Matas and Tom{\'a}ˇs Voj{\'i}˜r were supported by the Czech Science Foundation Project GACR P103/12/G084. Michael Felsberg and Gustav H{\"a}ger were supported by WASP, VR (EMC2), SSF (SymbiCloud), and SNIC. Roman Pflugfelder and Gustavo Fern{\'a}ndez were supported by the AIT Strategic Research Programme 2017 Visual Surveillance and Insight. The challenge was sponsored by Faculty of Computer Science, University of Ljubljana, Slovenia. Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 15th European Conference on Computer Vision, ECCV 2018 ; Conference date: 08-09-2018 Through 14-09-2018",

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address = "Germany",

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Kristan, M, Leonardis, A, Matas, J, Felsberg, M, Pflugfelder, R, Zajc, LČ, Vojír̃, T, Bhat, G, Lukežič, A, Eldesokey, A, Fernández, G, García-Martín, Á, Iglesias-Arias, Á, Alatan, AA, González-García, A, Petrosino, A, Memarmoghadam, A, Vedaldi, A, Muhič, A, He, A, Smeulders, A, Perera, AG, Li, B, Chen, B, Kim, C, Xu, C, Xiong, C, Tian, C, Luo, C, Sun, C, Hao, C, Kim, D, Mishra, D, Chen, D, Wang, D, Wee, D, Gavves, E, Gundogdu, E, Velasco-Salido, E, Khan, FS, Yang, F, Zhao, F, Li, F, Battistone, F, De Ath, G, Li, J, Wang, N, Tao, R, Zhang, T & Li, Y 2019, The sixth visual object tracking VOT2018 challenge results. in L Leal-Taixé & S Roth (eds), Computer Vision – ECCV 2018 Workshops, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11129 LNCS, Springer Verlag, pp. 3-53, 15th European Conference on Computer Vision, ECCV 2018, Munich, Germany, 09/8/18. https://doi.org/10.1007/978-3-030-11009-3_1

The sixth visual object tracking VOT2018 challenge results. / Kristan, Matej; Leonardis, Aleš; Matas, Jiří et al.
Computer Vision – ECCV 2018 Workshops, Proceedings. ed. / Laura Leal-Taixé; Stefan Roth. Springer Verlag, 2019. p. 3-53 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11129 LNCS).

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

TY - GEN

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AU - Kristan, Matej

AU - Leonardis, Aleš

AU - Matas, Jiří

AU - Felsberg, Michael

AU - Pflugfelder, Roman

AU - Zajc, Luka Čehovin

AU - Vojír̃, Tomáš

AU - Bhat, Goutam

AU - Lukežič, Alan

AU - Eldesokey, Abdelrahman

AU - Fernández, Gustavo

AU - García-Martín, Álvaro

AU - Iglesias-Arias, Álvaro

AU - Alatan, A. Aydin

AU - González-García, Abel

AU - Petrosino, Alfredo

AU - Memarmoghadam, Alireza

AU - Vedaldi, Andrea

AU - Muhič, Andrej

AU - He, Anfeng

AU - Smeulders, Arnold

AU - Perera, Asanka G.

AU - Li, Bo

AU - Chen, Boyu

AU - Kim, Changick

AU - Xu, Changsheng

AU - Xiong, Changzhen

AU - Tian, Cheng

AU - Luo, Chong

AU - Sun, Chong

AU - Hao, Cong

AU - Kim, Daijin

AU - Mishra, Deepak

AU - Chen, Deming

AU - Wang, Dong

AU - Wee, Dongyoon

AU - Gavves, Efstratios

AU - Gundogdu, Erhan

AU - Velasco-Salido, Erik

AU - Khan, Fahad Shahbaz

AU - Yang, Fan

AU - Zhao, Fei

AU - Li, Feng

AU - Battistone, Francesco

AU - De Ath, George

AU - Li, Jing

AU - Wang, Ning

AU - Tao, Ran

AU - Zhang, Tianzhu

AU - Li, Yan

N1 - Funding Information: 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 project J2-8175. Jiˇri Matas and Tomáˇs Vojí˜r were supported by the Czech Science Foundation Project GACR P103/12/G084. Michael Felsberg and Gustav Häger were supported by WASP, VR (EMC2), SSF (SymbiCloud), and SNIC. Roman Pflugfelder and Gustavo Fernández were supported by the AIT Strategic Research Programme 2017 Visual Surveillance and Insight. The challenge was sponsored by Faculty of Computer Science, University of Ljubljana, Slovenia. Publisher Copyright: © Springer Nature Switzerland AG 2019.

PY - 2019

Y1 - 2019

N2 - The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis and a “real-time” experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. A long-term tracking subchallenge has been introduced to the set of standard VOT sub-challenges. The new subchallenge focuses on long-term tracking properties, namely coping with target disappearance and reappearance. A new dataset has been compiled and a performance evaluation methodology that focuses on long-term tracking capabilities has been adopted. The VOT toolkit has been updated to support both standard short-term and the new long-term tracking subchallenges. 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 dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net).

AB - The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis and a “real-time” experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. A long-term tracking subchallenge has been introduced to the set of standard VOT sub-challenges. The new subchallenge focuses on long-term tracking properties, namely coping with target disappearance and reappearance. A new dataset has been compiled and a performance evaluation methodology that focuses on long-term tracking capabilities has been adopted. The VOT toolkit has been updated to support both standard short-term and the new long-term tracking subchallenges. 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 dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net).

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AN - SCOPUS:85061750502

SN - 9783030110086

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 3

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BT - Computer Vision – ECCV 2018 Workshops, Proceedings

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PB - Springer Verlag

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ER -

Kristan M, Leonardis A, Matas J, Felsberg M, Pflugfelder R, Zajc LČ et al. The sixth visual object tracking VOT2018 challenge results. In Leal-Taixé L, Roth S, editors, Computer Vision – ECCV 2018 Workshops, Proceedings. Springer Verlag. 2019. p. 3-53. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-11009-3_1

The sixth visual object tracking VOT2018 challenge results

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