The seventh visual object tracking VOT2019 challenge results

Matej Kristan; Jirí Matas; Ales Leonardis; Michael Felsberg; Roman Pflugfelder; Joni Kristian Kämäräinen; Luka Cehovin Zajc; Ondrej Drbohlav; Alan Lukezic; Amanda Berg; Abdelrahman Eldesokey; Jani Kapyla; Gustavo Fernández; Abel Gonzalez-Garcia; Alireza Memarmoghadam; Andong Lu; Anfeng He; Anton Varfolomieiev; Antoni Chan; Ardhendu Shekhar Tripathi; Arnold Smeulders; Bala Suraj Pedasingu; Bao Xin Chen; Baopeng Zhang; B. Baoyuanwu; Bi Li; Bin He; Bin Yan; Bing Bai; Bing Li; Bo Li; Byeong Hak Kim; Chao Ma; Chen Fang; Chen Qian; Cheng Chen; Chenglong Li; Chengquan Zhang; Chi Yi Tsai; Chong Luo; Christian Micheloni; Chunhui Zhang; Jie Chen; Jing Li; Li Zhang; Ming Tang; Pengfei Zhang; Qi Zhang Qiang Wang; Yang Liu; Yi Zhang

doi:10.1109/ICCVW.2019.00276

The seventh visual object tracking VOT2019 challenge results

Matej Kristan, Jirí Matas, Ales Leonardis, Michael Felsberg, Roman Pflugfelder, Joni Kristian Kämäräinen, Luka Cehovin Zajc, Ondrej Drbohlav, Alan Lukezic, Amanda Berg, Abdelrahman Eldesokey, Jani Kapyla, Gustavo Fernández, Abel Gonzalez-Garcia, Alireza Memarmoghadam, Andong Lu, Anfeng He, Anton Varfolomieiev, Antoni Chan, Ardhendu Shekhar TripathiArnold Smeulders, Bala Suraj Pedasingu, Bao Xin Chen, Baopeng Zhang, B. Baoyuanwu, Bi Li, Bin He, Bin Yan, Bing Bai, Bing Li, Bo Li, Byeong Hak Kim, Chao Ma, Chen Fang, Chen Qian, Cheng Chen, Chenglong Li, Chengquan Zhang, Chi Yi Tsai, Chong Luo, Christian Micheloni, Chunhui Zhang, Jie Chen, Jing Li, Li Zhang, Ming Tang, Pengfei Zhang, Qi Zhang Qiang Wang, Yang Liu, Yi Zhang

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

419 Scopus citations

Abstract

The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 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 as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOTST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on 'real-time' shortterm tracking in RGB, (iii) VOT-LT2019 focused on longterm tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard shortterm, long-term tracking and tracking with multi-channel imagery. 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.

Original language	English (US)
Title of host publication	Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2206-2241
Number of pages	36
ISBN (Electronic)	9781728150239
DOIs	https://doi.org/10.1109/ICCVW.2019.00276
State	Published - Oct 2019
Event	17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019 - Seoul, Korea, Republic of Duration: Oct 27 2019 → Oct 28 2019

Publication series

Name	Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019

Conference

Conference	17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019
Country/Territory	Korea, Republic of
City	Seoul
Period	10/27/19 → 10/28/19

Bibliographical note

Funding Information:
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. Jiˇi Matas and Ondrej Drbohlav were supported by the Czech Science Foundation Project GACR P103/12/G084. Alesˇ Leonardis was supported by MURI project financed by MoD/Dstl and EPSRC through EP/N019415/1 grant. Michael Felsberg, Amanda Berg, and Abdelrahman Eldesokey were supported by WASP, VR (ELLIIT, LÄST, and NCNN), and SSF (SymbiCloud). Roman Pflugfelder and Gustavo Fernández were supported by the AIT Strategic Research Programme 2019 Visual Surveillance and Insight. The challenge was sponsored by the Faculty of Computer Science, University of Ljubljana, Slovenia.

Publisher Copyright:
© 2019 IEEE.

Keywords

Object tracking
Performance evaluation
VOT challenge

ASJC Scopus subject areas

Computer Science Applications
Computer Vision and Pattern Recognition

Access to Document

10.1109/ICCVW.2019.00276

Cite this

Kristan, M., Matas, J., Leonardis, A., Felsberg, M., Pflugfelder, R., Kämäräinen, J. K., Zajc, L. C., Drbohlav, O., Lukezic, A., Berg, A., Eldesokey, A., Kapyla, J., Fernández, G., Gonzalez-Garcia, A., Memarmoghadam, A., Lu, A., He, A., Varfolomieiev, A., Chan, A., ... Zhang, Y. (2019). The seventh visual object tracking VOT2019 challenge results. In Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019 (pp. 2206-2241). Article 9022051 (Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCVW.2019.00276

@inproceedings{80f68f33abe943139f1bac33a692855c,

title = "The seventh visual object tracking VOT2019 challenge results",

abstract = "The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 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 as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOTST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on 'real-time' shortterm tracking in RGB, (iii) VOT-LT2019 focused on longterm tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard shortterm, long-term tracking and tracking with multi-channel imagery. 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.",

keywords = "Object tracking, Performance evaluation, VOT challenge",

author = "Matej Kristan and Jir{\'i} Matas and Ales Leonardis and Michael Felsberg and Roman Pflugfelder and K{\"a}m{\"a}r{\"a}inen, {Joni Kristian} and Zajc, {Luka Cehovin} and Ondrej Drbohlav and Alan Lukezic and Amanda Berg and Abdelrahman Eldesokey and Jani Kapyla and Gustavo Fern{\'a}ndez and Abel Gonzalez-Garcia and Alireza Memarmoghadam and Andong Lu and Anfeng He and Anton Varfolomieiev and Antoni Chan and Tripathi, {Ardhendu Shekhar} and Arnold Smeulders and Pedasingu, {Bala Suraj} and Chen, {Bao Xin} and Baopeng Zhang and B. Baoyuanwu and Bi Li and Bin He and Bin Yan and Bing Bai and Bing Li and Bo Li and Kim, {Byeong Hak} and Chao Ma and Chen Fang and Chen Qian and Cheng Chen and Chenglong Li and Chengquan Zhang and Tsai, {Chi Yi} and Chong Luo and Christian Micheloni and Chunhui Zhang and Jie Chen and Jing Li and Li Zhang and Ming Tang and Pengfei Zhang and Wang, {Qi Zhang Qiang} and Yang Liu and Yi Zhang",

note = "Funding Information: 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. Jiˇi Matas and Ondrej Drbohlav were supported by the Czech Science Foundation Project GACR P103/12/G084. Alesˇ Leonardis was supported by MURI project financed by MoD/Dstl and EPSRC through EP/N019415/1 grant. Michael Felsberg, Amanda Berg, and Abdelrahman Eldesokey were supported by WASP, VR (ELLIIT, L{\"A}ST, and NCNN), and SSF (SymbiCloud). Roman Pflugfelder and Gustavo Fern{\'a}ndez were supported by the AIT Strategic Research Programme 2019 Visual Surveillance and Insight. The challenge was sponsored by the Faculty of Computer Science, University of Ljubljana, Slovenia. Publisher Copyright: {\textcopyright} 2019 IEEE.; 17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019 ; Conference date: 27-10-2019 Through 28-10-2019",

year = "2019",

month = oct,

doi = "10.1109/ICCVW.2019.00276",

language = "English (US)",

series = "Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2206--2241",

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Kristan, M, Matas, J, Leonardis, A, Felsberg, M, Pflugfelder, R, Kämäräinen, JK, Zajc, LC, Drbohlav, O, Lukezic, A, Berg, A, Eldesokey, A, Kapyla, J, Fernández, G, Gonzalez-Garcia, A, Memarmoghadam, A, Lu, A, He, A, Varfolomieiev, A, Chan, A, Tripathi, AS, Smeulders, A, Pedasingu, BS, Chen, BX, Zhang, B, Baoyuanwu, B, Li, B, He, B, Yan, B, Bai, B, Li, B, Li, B, Kim, BH, Ma, C, Fang, C, Qian, C, Chen, C, Li, C, Zhang, C, Tsai, CY, Luo, C, Micheloni, C, Zhang, C, Chen, J, Li, J, Zhang, L, Tang, M, Zhang, P, Wang, QZQ , Liu, Y & Zhang, Y 2019, The seventh visual object tracking VOT2019 challenge results. in Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019., 9022051, Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019, Institute of Electrical and Electronics Engineers Inc., pp. 2206-2241, 17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019, Seoul, Korea, Republic of, 10/27/19. https://doi.org/10.1109/ICCVW.2019.00276

The seventh visual object tracking VOT2019 challenge results. / Kristan, Matej; Matas, Jirí; Leonardis, Ales et al.
Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 2206-2241 9022051 (Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019).

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

TY - GEN

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AU - Kristan, Matej

AU - Matas, Jirí

AU - Leonardis, Ales

AU - Felsberg, Michael

AU - Pflugfelder, Roman

AU - Kämäräinen, Joni Kristian

AU - Zajc, Luka Cehovin

AU - Drbohlav, Ondrej

AU - Lukezic, Alan

AU - Berg, Amanda

AU - Eldesokey, Abdelrahman

AU - Kapyla, Jani

AU - Fernández, Gustavo

AU - Gonzalez-Garcia, Abel

AU - Memarmoghadam, Alireza

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AU - He, Anfeng

AU - Varfolomieiev, Anton

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AU - Tripathi, Ardhendu Shekhar

AU - Smeulders, Arnold

AU - Pedasingu, Bala Suraj

AU - Chen, Bao Xin

AU - Zhang, Baopeng

AU - Baoyuanwu, B.

AU - Li, Bi

AU - He, Bin

AU - Yan, Bin

AU - Bai, Bing

AU - Li, Bing

AU - Li, Bo

AU - Kim, Byeong Hak

AU - Ma, Chao

AU - Fang, Chen

AU - Qian, Chen

AU - Chen, Cheng

AU - Li, Chenglong

AU - Zhang, Chengquan

AU - Tsai, Chi Yi

AU - Luo, Chong

AU - Micheloni, Christian

AU - Zhang, Chunhui

AU - Chen, Jie

AU - Li, Jing

AU - Zhang, Li

AU - Tang, Ming

AU - Zhang, Pengfei

AU - Wang, Qi Zhang Qiang

AU - Liu, Yang

AU - Zhang, Yi

N1 - Funding Information: 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. Jiˇi Matas and Ondrej Drbohlav were supported by the Czech Science Foundation Project GACR P103/12/G084. Alesˇ Leonardis was supported by MURI project financed by MoD/Dstl and EPSRC through EP/N019415/1 grant. Michael Felsberg, Amanda Berg, and Abdelrahman Eldesokey were supported by WASP, VR (ELLIIT, LÄST, and NCNN), and SSF (SymbiCloud). Roman Pflugfelder and Gustavo Fernández were supported by the AIT Strategic Research Programme 2019 Visual Surveillance and Insight. The challenge was sponsored by the Faculty of Computer Science, University of Ljubljana, Slovenia. Publisher Copyright: © 2019 IEEE.

PY - 2019/10

Y1 - 2019/10

N2 - The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 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 as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOTST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on 'real-time' shortterm tracking in RGB, (iii) VOT-LT2019 focused on longterm tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard shortterm, long-term tracking and tracking with multi-channel imagery. 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.

AB - The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 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 as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOTST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on 'real-time' shortterm tracking in RGB, (iii) VOT-LT2019 focused on longterm tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard shortterm, long-term tracking and tracking with multi-channel imagery. 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.

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KW - Performance evaluation

KW - VOT challenge

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M3 - Conference contribution

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T3 - Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019

SP - 2206

EP - 2241

BT - Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019

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Kristan M, Matas J, Leonardis A, Felsberg M, Pflugfelder R, Kämäräinen JK et al. The seventh visual object tracking VOT2019 challenge results. In Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 2206-2241. 9022051. (Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019). doi: 10.1109/ICCVW.2019.00276

The seventh visual object tracking VOT2019 challenge results

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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