FuCoLoT -- A Fully-Correlational Long-Term Tracker

We propose FuCoLoT -- a Fully Correlational Long-term Tracker. It 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 ac...

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Bibliographic Details
Published in:arXiv.org 2019-01
Main Authors: Lukežič, Alan, Zajc, Luka Čehovin, Vojíř, Tomáš, Matas, Jiří, Kristan, Matej
Format: Article
Language:English
Subjects:
Benchmarks
Correlation
Image detection
Sensors
Short term
State of the art
Target detection
Target recognition
Online Access:Get full text
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Summary:We propose FuCoLoT -- a Fully Correlational Long-term Tracker. It 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.
ISSN:2331-8422