Object Tracking in Satellite Videos Based on a Multiframe Optical Flow Tracker

Object tracking is a hot topic in computer vision. Thanks to the booming of the very high resolution (VHR) remote sensing techniques, it is now possible to track targets of interests in satellite videos. However, since the targets in the satellite videos are usually too small in comparison with the entire image, and too similar with the background, most state-of-the-art algorithms failed to track the target in satellite videos with a satisfactory accuracy. Due to the fact that optical flow shows great potential to detect even the slight movement of the targets, we proposed a multiframe optical flow tracker for object tracking in satellite videos. The Lucas-Kanade optical flow method was fused with the HSV color system and integral image to track the targets in the satellite videos, while multiframe difference method was utilized in the optical flow tracker for a better interpretation. The experiments with five VHR remote sensing satellite video datasets indicate that compared with state-of-the-art object tracking algorithms, the proposed method can track the target more accurately.