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

134 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
Kristan, Matej ; Pflugfelder, Roman ; Leonardis, Ales ; Matas, Jiri ; Porikli, Fatih ; Cehovin, Luka ; Nebehay, Georg ; Fernandez, Gustavo ; Vojir, Tomas ; Gatt, Adam ; Khajenezhad, Ahmad ; Salahledin, Ahmed ; Soltani-Farini, Ali ; Zarezade, Ali ; Petrosino, Alfredo ; Milton, Anthony ; BOZORGTABAR, Behzad ; Li, Bo ; Chan, Chee ; Heng, CherKeng ; Ward, Dale ; Kearney, David ; Monekosso, Dorothy ; Karaimer, Hakki ; Rabiee, Hamid ; Zhu, Jianke ; Gao, Jin ; Xiao, Jingjing ; Zhang, Junge ; Xing, Junliang ; Huang, Kaiqi ; Lebeda, Karel ; Cao, Lijun ; Maresca, Mario ; Lim, Mei ; El Helw, Mohamed ; Felsberg, Michael ; Remanginino, Paolo ; Bowden, Richard ; GOECKE, Roland ; Stolkin, Rustam ; Lim, Samantha ; Maher, Sara ; Poullot, Sebastien ; Wong, Sebastien ; Satoh, Shin'ichi ; Chen, Weihua ; Hu, Weiming ; Zhang, Xiaoqin ; Li, Yang ; Niu, ZhiHeng. / The visual object tracking VOT2013 challenge results. 2013 IEEE International conference on computer vision workshops. editor / Patrick Kellenberger. USA : IEEE, Institute of Electrical and Electronics Engineers, 2013. pp. 98-111
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Kristan, M, Pflugfelder, R, Leonardis, A, Matas, J, Porikli, F, Cehovin, L, Nebehay, G, Fernandez, G, Vojir, T, Gatt, A, Khajenezhad, A, Salahledin, A, Soltani-Farini, A, Zarezade, A, Petrosino, A, Milton, A, BOZORGTABAR, B, Li, B, Chan, C, Heng, C, Ward, D, Kearney, D, Monekosso, D, Karaimer, H, Rabiee, H, Zhu, J, Gao, J, Xiao, J, Zhang, J, Xing, J, Huang, K, Lebeda, K, Cao, L, Maresca, M, Lim, M, El Helw, M, Felsberg, M, Remanginino, P, Bowden, R, GOECKE, R, Stolkin, R, Lim, S, Maher, S, Poullot, S, Wong, S, Satoh, S, Chen, W, Hu, W, Zhang, X, Li, Y & Niu, Z 2013, The visual object tracking VOT2013 challenge results. in P Kellenberger (ed.), 2013 IEEE International conference on computer vision workshops. IEEE, Institute of Electrical and Electronics Engineers, USA, pp. 98-111, 2013 IEEE International conference on computer vision workshops, Sydney, Australia, 2/12/13. https://doi.org/10.1109/ICCVW.2013.20

The visual object tracking VOT2013 challenge results. / Kristan, Matej; Pflugfelder, Roman; Leonardis, Ales; Matas, Jiri; Porikli, Fatih; Cehovin, Luka; Nebehay, Georg; Fernandez, Gustavo; Vojir, Tomas; Gatt, Adam; Khajenezhad, Ahmad; Salahledin, Ahmed; Soltani-Farini, Ali; Zarezade, Ali; Petrosino, Alfredo; Milton, Anthony; BOZORGTABAR, Behzad; Li, Bo; Chan, Chee; Heng, CherKeng; Ward, Dale; Kearney, David; Monekosso, Dorothy; Karaimer, Hakki; Rabiee, Hamid; Zhu, Jianke; Gao, Jin; Xiao, Jingjing; Zhang, Junge; Xing, Junliang; Huang, Kaiqi; Lebeda, Karel; Cao, Lijun; Maresca, Mario; Lim, Mei; El Helw, Mohamed; Felsberg, Michael; Remanginino, Paolo; Bowden, Richard; GOECKE, Roland; Stolkin, Rustam; Lim, Samantha; Maher, Sara; Poullot, Sebastien; Wong, Sebastien; Satoh, Shin'ichi; Chen, Weihua; Hu, Weiming; Zhang, Xiaoqin; Li, Yang; Niu, ZhiHeng.

2013 IEEE International conference on computer vision workshops. ed. / Patrick Kellenberger. USA : IEEE, Institute of Electrical and Electronics Engineers, 2013. p. 98-111.

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

TY - GEN

T1 - The visual object tracking VOT2013 challenge results

AU - Kristan, Matej

AU - Pflugfelder, Roman

AU - Leonardis, Ales

AU - Matas, Jiri

AU - Porikli, Fatih

AU - Cehovin, Luka

AU - Nebehay, Georg

AU - Fernandez, Gustavo

AU - Vojir, Tomas

AU - Gatt, Adam

AU - Khajenezhad, Ahmad

AU - Salahledin, Ahmed

AU - Soltani-Farini, Ali

AU - Zarezade, Ali

AU - Petrosino, Alfredo

AU - Milton, Anthony

AU - BOZORGTABAR, Behzad

AU - Li, Bo

AU - Chan, Chee

AU - Heng, CherKeng

AU - Ward, Dale

AU - Kearney, David

AU - Monekosso, Dorothy

AU - Karaimer, Hakki

AU - Rabiee, Hamid

AU - Zhu, Jianke

AU - Gao, Jin

AU - Xiao, Jingjing

AU - Zhang, Junge

AU - Xing, Junliang

AU - Huang, Kaiqi

AU - Lebeda, Karel

AU - Cao, Lijun

AU - Maresca, Mario

AU - Lim, Mei

AU - El Helw, Mohamed

AU - Felsberg, Michael

AU - Remanginino, Paolo

AU - Bowden, Richard

AU - GOECKE, Roland

AU - Stolkin, Rustam

AU - Lim, Samantha

AU - Maher, Sara

AU - Poullot, Sebastien

AU - Wong, Sebastien

AU - Satoh, Shin'ichi

AU - Chen, Weihua

AU - Hu, Weiming

AU - Zhang, Xiaoqin

AU - Li, Yang

AU - Niu, ZhiHeng

PY - 2013

Y1 - 2013

N2 - 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).

AB - 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).

KW - visual object tracking

U2 - 10.1109/ICCVW.2013.20

DO - 10.1109/ICCVW.2013.20

M3 - Conference contribution

SN - 9781479930227

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EP - 111

BT - 2013 IEEE International conference on computer vision workshops

A2 - Kellenberger, Patrick

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - USA

ER -

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