FCLT - A Fully-Correlational Long-Term Tracker

نویسندگان

  • Alan Lukezic
  • Luka Cehovin Zajc
  • Tomás Vojír
  • Jiri Matas
  • Matej Kristan
چکیده

We propose FCLT – a fully-correlational long-term tracker. The two main components of FCLT are a shortterm tracker which localizes the target in each frame and a detector which re-detects the target when it is lost. Both the short-term tracker and the detector are based on correlation filters. The detector exploits properties of the recent constrained filter learning and is able to re-detect the target in the whole image efficiently. A failure detection mechanism based on correlation response quality is proposed. The FCLT is tested on recent short-term and long-term benchmarks. It achieves state-of-the-art results on the short-term benchmarks and it outperforms the current best-performing tracker on the long-term benchmark by over 18%.

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عنوان ژورنال:
  • CoRR

دوره abs/1711.09594  شماره 

صفحات  -

تاریخ انتشار 2017