Paper
15 February 2022 Improved SORT for vehicles tracking in satellite videos
Shuanglin Wu, Jungang Yang, Chao Xiao, Qian Yin, Ruojing Li, Yaoyuan Zeng, Wei An
Author Affiliations +
Proceedings Volume 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021); 121665H (2022) https://doi.org/10.1117/12.2617540
Event: Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 2021, Hong Kong, Hong Kong
Abstract
Multi-object tracking in satellite videos has been widely used in civilian and military fields. Among them, the tracking of vehicles has important applications in the field of traffic monitoring. However, the tracking of vehicles in satellite videos still remains challenging and unsolved due to the extremely small size and the lack of appearance and geometric features. In this paper, we propose an improved SORT to tackle the tracking of vehicles in satellite videos by introducing C3D to CenterNet to improve the detection performance and promote the overall tracking performance. Specifically, we use C3D as the backbone of CenterNet to extract spatio-temporal information and use a 3D channel attention mechanism to fuse the information extracted by C3D to improve the detection performance, thereby improving the tracking results. The qualitative and quantitative results of experiments on videos of Jilin-1 satellite constellation show that our method can efficiently improve the tracking performance of vehicles in satellite videos.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shuanglin Wu, Jungang Yang, Chao Xiao, Qian Yin, Ruojing Li, Yaoyuan Zeng, and Wei An "Improved SORT for vehicles tracking in satellite videos", Proc. SPIE 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 121665H (15 February 2022); https://doi.org/10.1117/12.2617540
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KEYWORDS
Satellites

Video

Video surveillance

Feature extraction

Satellite imaging

Convolution

Data modeling

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