Journal article

HRSiam: High-Resolution Siamese Network, Towards Space-Borne Satellite Video Tracking

Jia Shao, Bo Du, Chen Wu, Mingming Gong, Tongliang Liu

IEEE TRANSACTIONS ON IMAGE PROCESSING | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | Published : 2021

Abstract

Tracking moving objects from space-borne satellite videos is a new and challenging task. The main difficulty stems from the extremely small size of the target of interest. First, because the target usually occupies only a few pixels, it is hard to obtain discriminative appearance features. Second, the small object can easily suffer from occlusion and illumination variation, making the features of objects less distinguishable from features in surrounding regions. Current state-of-the-art tracking approaches mainly consider high-level deep features of a single frame with low spatial resolution, and hardly benefit from inter-frame motion information inherent in videos. Thus, they fail to accura..

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University of Melbourne Researchers

Grants

Awarded by National Natural Science Foundation of China


Awarded by Natural Science Foundation of Hubei Province


Awarded by Science and Technology Major Project of Hubei Province (NextGeneration AI Technologies)


Funding Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant 61822113, Grant 41871243, and Grant 61971317, in part by the Natural Science Foundation of Hubei Province under Grant 2018CFA050 and Grant 2020CFB594, and in part by the Science and Technology Major Project of Hubei Province (NextGeneration AI Technologies) under Grant 2019AEA170. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Weiyao Lin.