Moving ship detection of satellite video based on a weakly supervised detector

Zhuang Zhou; Shengyang Li; Xuan Li; Yunziwei Deng

doi:10.1117/12.2678290

19 October 2023 Moving ship detection of satellite video based on a weakly supervised detector

Zhuang Zhou, Shengyang Li, Xuan Li, Yunziwei Deng

Proceedings Volume 12733, Image and Signal Processing for Remote Sensing XXIX; 127330L (2023) https://doi.org/10.1117/12.2678290
Event: SPIE Remote Sensing, 2023, Amsterdam, Netherlands

Abstract

Restricted by the limited accessible data resources and the high cost of frame-by-frame labeling, fully supervised object detection is difficult to meet the needs of satellite video applications. In this paper, we propose a weakly-supervised satellite video detector based on salient feature fusion and boundary noise exploitation that enables moving ship detection without relying on object instance labeling. To mitigate pseudo-motion disturbances such as background movement, waves, and illumination changes, we first construct salient fusion features and then use Gaussian background modeling to generate high-quality pseudo-labels. To fully exploit the boundary information of noisy masks in pseudo label, we improve the Mask R-CNN by designing a noise-tolerant branch that fuses low-resolution features to mitigate the interference of inaccurate mask boundaries and guiding the network to learn boundary-related region features through boundary preserving mapping to enable better alignment of the predicted mask with the actual object. The experimental evaluation results show that the proposed method significantly outperforms other weakly supervised moving object detection methods and achieves comparable performance to fully supervised method.

Conference Presentation

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhuang Zhou, Shengyang Li, Xuan Li, and Yunziwei Deng "Moving ship detection of satellite video based on a weakly supervised detector", Proc. SPIE 12733, Image and Signal Processing for Remote Sensing XXIX, 127330L (19 October 2023); https://doi.org/10.1117/12.2678290

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available