The visual object tracking VOT2013 challenge results

Matej Kristan, Roman Pflugfelder, Ales Leonardis, Jiri Matas, Fatih Porikli, Luka Cehovin, Georg Nebehay, Gustavo Fernandez, Tomas Vojir, Adam Gatt, Ahmad Khajenezhad, Ahmed Salahledin, Ali Soltani-Farini, Ali Zarezade, Alfredo Petrosino, Anthony Milton, Behzad BOZORGTABAR, Bo Li, Chee Chan, CherKeng Heng & 31 others Dale Ward, David Kearney, Dorothy Monekosso, Hakki Karaimer, Hamid Rabiee, Jianke Zhu, Jin Gao, Jingjing Xiao, Junge Zhang, Junliang Xing, Kaiqi Huang, Karel Lebeda, Lijun Cao, Mario Maresca, Mei Lim, Mohamed El Helw, Michael Felsberg, Paolo Remanginino, Richard Bowden, Roland GOECKE, Rustam Stolkin, Samantha Lim, Sara Maher, Sebastien Poullot, Sebastien Wong, Shin'ichi Satoh, Weihua Chen, Weiming Hu, Xiaoqin Zhang, Yang Li, ZhiHeng Niu

Research output: A Conference proceeding or a Chapter in BookConference contribution

152 Citations (Scopus)

Abstract

Visual tracking has attracted a significant attention in the last few decades. The recent surge in the number of publications on tracking-related problems have made it almost impossible to follow the developments in the field. One of the reasons is that there is a lack of commonly accepted annotated data-sets and standardized evaluation protocols that would allow objective comparison of different tracking methods. To address this issue, the Visual Object Tracking (VOT) workshop was organized in conjunction with ICCV2013. Researchers from academia as well as industry were invited to participate in the first VOT2013 challenge which aimed at single-object visual trackers that do not apply pre-learned models of object appearance (model-free). Presented here is the VOT2013 benchmark dataset for evaluation of single-object visual trackers as well as the results obtained by the trackers competing in the challenge. In contrast to related attempts in tracker benchmarking, the dataset is labeled per-frame by visual attributes that indicate occlusion, illumination change, motion change, size change and camera motion, offering a more systematic comparison of the trackers. Furthermore, we have designed an automated system for performing and evaluating the experiments. We present the evaluation protocol of the VOT2013 challenge and the results of a comparison of 27 trackers on the benchmark dataset. The dataset, the evaluation tools and the tracker rankings are publicly available from the challenge website (http://votchallenge.net).
Original languageEnglish
Title of host publication2013 IEEE International conference on computer vision workshops
EditorsPatrick Kellenberger
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages98-111
Number of pages14
ISBN (Electronic)9781479930227
ISBN (Print)9781479930227
DOIs
Publication statusPublished - 2013
Event2013 IEEE International conference on computer vision workshops - Sydney, Sydney, Australia
Duration: 2 Dec 20138 Dec 2013

Workshop

Workshop2013 IEEE International conference on computer vision workshops
CountryAustralia
CitySydney
Period2/12/138/12/13

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Kristan, M., Pflugfelder, R., Leonardis, A., Matas, J., Porikli, F., Cehovin, L., ... Niu, Z. (2013). The visual object tracking VOT2013 challenge results. In P. Kellenberger (Ed.), 2013 IEEE International conference on computer vision workshops (pp. 98-111). USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICCVW.2013.20