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 proceedingConference contributionpeer-review

188 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 languageEnglish (US)
Title of host publicationComputer Vision – ECCV 2018 Workshops, Proceedings
EditorsLaura Leal-Taixé, Stefan Roth
PublisherSpringer Verlag
Pages3-53
Number of pages51
ISBN (Print)9783030110086
DOIs
StatePublished - 2019
Event15th European Conference on Computer Vision, ECCV 2018 - Munich, Germany
Duration: Sep 8 2018Sep 14 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11129 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th European Conference on Computer Vision, ECCV 2018
Country/TerritoryGermany
CityMunich
Period09/8/1809/14/18

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

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