作者
Matej Kristan,Roman Pflugfelder,Ales Leonardis,Jiri Matas,Luka Cehovin,Georg Nebehay,Tomas Vojir,Gustavo Fernández,Alan Lukezic,Aleksandar Dimitriev,Alfredo Petrosino,Amir Saffari,Bo Li,Bohyung Han,Cher-Keng Heng,Christophe Garcia,Dominik Pangersic,Gustav Häger,Fahad Shahbaz Khan,Franci Oven,Horst Possegger,Horst Bischof,Hyeonseob Nam,Jianke Zhu,Jijia Li,Jin-Young Choi,Jin-Young Choi,João Antonio Pêgas Henriques,Joost van de Weijer,Jorge Batista,Karel Lebeda,Kristoffer Öfjäll,Kwang Moo Yi,Lei Qin,Longyin Wen,Mario Maresca,Martin Danelljan,Michael Felsberg,Ming-Ming Cheng,Philip H. S. Torr,Qingming Huang,Richard Bowden,Sam Hare,Samantha Yueying Lim,Seunghoon Hong,Shengcai Liao,Simon Hadfield,Stan Z. Li,Stefan Duffner,Stuart Golodetz,Thomas Mauthner,Vibhav Vineet,Weiyao Lin,Yan Li,Yuankai Qi,Zhen Lei,Zhi Ping Niu
摘要
The Visual Object Tracking challenge 2014, VOT2014, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 38 trackers are presented. The number of tested trackers makes VOT 2014 the largest benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the appendix. Features of the VOT2014 challenge that go beyond its VOT2013 predecessor are introduced: (i) a new VOT2014 dataset with full annotation of targets by rotated bounding boxes and per-frame attribute, (ii) extensions of the VOT2013 evaluation methodology, (iii) a new unit for tracking speed assessment less dependent on the hardware and (iv) the VOT2014 evaluation toolkit that significantly speeds up execution of experiments. The dataset, the evaluation kit as well as the results are publicly available at the challenge website ( http://votchallenge.net ).