FuCoLoT - A Fully-Correlational Long-Term Tracker

Asian Conference on Computer Vision, 2018
A Fully Correlational Long-term Tracker (FuCoLoT) exploits the novel DCF constrained filter learning method to design a detector that is able to re-detect the target in the whole image efficiently. FuCoLoT maintains several correlation filters trained on different time scales that act as the detector components. A novel mechanism based on the correlation response is used for tracking failure estimation. FuCoLoT achieves state-of-the-art results on standard short-term benchmarks and it outperforms the current best-performing tracker on the long-term UAV20L benchmark by over 19\%. It has an order of magnitude smaller memory footprint than its best-performing competitors and runs at 15fps in a single CPU thread.


<a href="http://prints.vicos.si/publications/366">FuCoLoT - A Fully-Correlational Long-Term Tracker</a>