A General Target Tracking and Sample Generation Framework for Satellite Videos Leveraging on Geometry-Aware Low-Rank Representation

Video satellites observe the Earth with high spatial-temporal resolution, empowering remote sensing with better capability for emergency needs. The tracking of moving targets naturally has received a great deal of attention. Many methods are proposed and achieve satisfying results after years of res...

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Bibliographic Details
Published inIGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium pp. 5886 - 5889
Main Authors Zhao, Xuhui, Huang, Ziqian, Zhao, Anqi, Li, Ziyao, Gao, Zhi
Format Conference Proceeding
LanguageEnglish
Published IEEE 16.07.2023
Subjects
Annotations
Distortion
Earth
Low-rank Representation
Remote sensing
Satellites
Target tracking
Video Satellite
Video sequences
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Summary:Video satellites observe the Earth with high spatial-temporal resolution, empowering remote sensing with better capability for emergency needs. The tracking of moving targets naturally has received a great deal of attention. Many methods are proposed and achieve satisfying results after years of research, where the low-rank representation (LRR) shows great potential due to its weak assumptions on data. However, the original LRR lacks the consideration of frame-wise geometric inconsistency led by imperfect video stabilization, significant view change, and elevation difference, resulting in pseudo-motion and declined performance on some video sequences. Therefore, we propose a geometry-aware LRR (Geo-LRR) that simultaneously considers the alignment and the target tracking in videos. Moreover, to relieve the dilemma of high-quality samples, we generate pixel-wise annotations with straightforward post-processing on sparse images. Extensive experiments demonstrate the effectiveness of our method with 2.051 pixel-wise RMSE compared with groundtruth.
ISSN:2153-7003
DOI:10.1109/IGARSS52108.2023.10281801