Abstract
As a new method of Earth observation, video satellite is capable of monitoring specific events on the Earth's surface continuously by providing high-temporal resolution remote sensing images. The video observations enable a variety of new satellite applications such as object tracking and road traffic monitoring. In this article, we address the problem of fast object tracking in satellite videos, by developing a novel tracking algorithm based on correlation filters embedded with motion estimations. Based on the kernelized correlation filter (KCF), the proposed algorithm provides the following improvements: 1) proposing a novel motion estimation (ME) algorithm by combining the Kalman filter and motion trajectory averaging and mitigating the boundary effects of KCF by using this ME algorithm and 2) solving the problem of tracking failure when a moving object is partially or completely occluded. The experimental results demonstrate that our algorithm can track the moving object in satellite videos with 95% accuracy.
Highlights
T HE launch of video satellites has enabled us to observe and measure moving objects on the Earth’s surface, which provides rich information for monitoring rapid-changing events, such as oil reserve detection, disaster monitoring, ocean monitoring, ecosystem disturbance monitoring, and traffic condition monitoring [1], [2]
In order to achieve high accuracy moving object tracking in satellite videos, we propose a correlation filter with the motion estimation (ME) algorithm (CFME)
Compared with KCF, the performance of correlation filter with motion estimation (CFME) is better, which proves that our improvement of KCF is effective in tracking large moving objects in satellite videos
Summary
T HE launch of video satellites has enabled us to observe and measure moving objects on the Earth’s surface, which provides rich information for monitoring rapid-changing events, such as oil reserve detection, disaster monitoring, ocean monitoring, ecosystem disturbance monitoring, and traffic condition monitoring [1], [2]. Among the analysis of satellite videos, moving object detection and tracking is highly demanded, which targets to locate moving objects on the surface and compute their trajectories [3]–[6]. The moving objects in satellite videos mainly include motor vehicles, airplanes, and ships.
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