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Parallel tracker for visual object tracking

In this paper, we present a novel tracker for real-time single object tracking by combining Kernelized Correlation Filter (KCF) and Distractor Aware Tracker (DAT). KCF is capable of distinguishing object from background efficiently while DAT is robust for object's appearance and similar distracting reigons. First, we propose a series­parallel connection structure to make full use of the two trackers's complementary advantages, which aims to locate the object position more accurately. Second, we add a revised scale filter to adapt the scale change. Experiments on OTB-100 demonstrate that our approach is better than both two sub-trackers and can run in real-time.