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Object Tracking Based on Satellite Videos: A Literature Review

Zhang, Z., Wang, C., Song, J. ORCID: 0000-0003-0623-0395 & Xu, Y. (2022). Object Tracking Based on Satellite Videos: A Literature Review. Remote Sensing, 14(15), article number 3674. doi: 10.3390/rs14153674

Abstract

Video satellites have recently become an attractive method of Earth observation, providing consecutive images of the Earth’s surface for continuous monitoring of specific events. The development of on-board optical and communication systems has enabled the various applications of satellite image sequences. However, satellite video-based target tracking is a challenging research topic in remote sensing due to its relatively low spatial and temporal resolution. Thus, this survey systematically investigates current satellite video-based tracking approaches and benchmark datasets, focusing on five typical tracking applications: traffic target tracking, ship tracking, typhoon tracking, fire tracking, and ice motion tracking. The essential aspects of each tracking target are summarized, such as the tracking architecture, the fundamental characteristics, primary motivations, and contributions. Furthermore, popular visual tracking benchmarks and their respective properties are discussed. Finally, a revised multi-level dataset based on WPAFB videos is generated and quantitatively evaluated for future development in the satellite video-based tracking area. In addition, 54.3% of the tracklets with lower Difficulty Score (DS) are selected and renamed as the Easy group, while 27.2% and 18.5% of the tracklets are grouped into the Medium-DS group and the Hard-DS group, respectively.

Publication Type: Article
Additional Information: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Publisher Keywords: satellite video; traffic target tracking; ship tracking; typhoon tracking; fire tracking; ice motion tracking; deep learning
Subjects: G Geography. Anthropology. Recreation > GB Physical geography
G Geography. Anthropology. Recreation > GE Environmental Sciences
Q Science > QC Physics
T Technology > T Technology (General)
Departments: School of Science & Technology > Engineering
SWORD Depositor:
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