Satellite Video Tracking by Multi-Feature Correlation Filters with Motion Estimation

As a novel method of earth observation, video satellites can observe dynamic changes in ground targets in real time. To make use of satellite videos, target tracking in satellite videos has received extensive interest. However, this also faces a variety of new challenges such as global occlusion, lo...

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Vydané v:Remote sensing (Basel, Switzerland) Ročník 14; číslo 11; s. 2691
Hlavní autori: Zhang, Yan, Chen, Deng, Zheng, Yuhui
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.06.2022
Predmet:
Algorithms
Background noise
correlation filter
disruptor-aware mechanism
Histograms
Kalman filters
motion estimation
Motion simulation
Noise
object tracking
Occlusion
Optical flow (image analysis)
Satellite observation
Satellite tracking
satellite video
Satellites
Video
ISSN:2072-4292, 2072-4292
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Popis
Shrnutí:As a novel method of earth observation, video satellites can observe dynamic changes in ground targets in real time. To make use of satellite videos, target tracking in satellite videos has received extensive interest. However, this also faces a variety of new challenges such as global occlusion, low resolution, and insufficient information compared with traditional target tracking. To handle the abovementioned problems, a multi-feature correlation filter with motion estimation is proposed. First, we propose a motion estimation algorithm that combines a Kalman filter and an inertial mechanism to alleviate the boundary effects. This can also be used to track the occluded target. Then, we fuse a histogram of oriented gradient (HOG) features and optical flow (OF) features to improve the representation information of the target. Finally, we introduce a disruptor-aware mechanism to weaken the influence of background noise. Experimental results verify that our algorithm can achieve high tracking performance.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2072-4292
2072-4292
DOI:10.3390/rs14112691