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Recently, correlation filters have yielded lots of promising results in the field of target tracking. However, when dealing with object tracking in satellite video, KCF tracker achieves poor results, because the size of the target is too small compared with the whole image, and the target and background are exactly similar. So, in this paper, we introduce the KCF tracker to the satellite video and propose the three frame difference algorithm to improve the performance of KCF tracker. For the purpose of reducing the probability of drifting in KCF tracker, a simple but effective target detection method: three frame difference algorithm is utilized to locate the target every once a few frames. Based on combining the KCF tracker and three frame difference algorithm, the proposed tracker achieves outperform top ranking trackers such as Struck and TLD on two datasets.

Object Tracking for Satellite Video based on Kernelized Correlation Filters and Three Frame Difference