The visual object tracking VOT2016 challenge results

The visual object tracking VOT2016 challenge results

The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals i...

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Bibliographic Details
Main Authors: Kristan, M, Leonardis, A, Matas, J, Felsberg, M, Pflugfelder, R, Čehovin, L, Vojír̃, T, Häger, G, Lukežič, A, Fernández, G, Gupta, A, Petrosino, A, Memarmoghadam, A, Garcia-Martin, A, Solís Montero, A, Vedaldi, A, Robinson, A, Ma, AJ, Varfolomieiev, A, Alatan, A, Erdem, A, Ghanem, B, Liu, B, Han, B, Martinez, B, Chang, C-M, Xu, C, Sun, C, Kim, D, Chen, D, Du, D, Mishra, D, Yeung, D-Y, Gundogdu, E, Erdem, E, Khan, F, Porikli, F, Zhao, F, Bunyak, F, Battistone, F, Zhu, G, Roffo, G, Subrahmanyam, GRKS, Bastos, G, Seetharaman, G, Medeiros, H, Li, H, Qi, H, Bischof, H, Possegger, H, Henriques, JF, Torr, PHS
Format: Conference item
Language:English
Published: Springer 2016
Description
Summary:The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals in the recent years. The number of tested state-of-the-art trackers makes the VOT 2016 the largest and most challenging benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the Appendix. The VOT2016 goes beyond its predecessors by (i) introducing a new semi-automatic ground truth bounding box annotation methodology and (ii) extending the evaluation system with the no-reset experiment. The dataset, the evaluation kit as well as the results are publicly available at the challenge website (http: //votchallenge.net).

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