Remote sensing image ship detection based on feature pyramid

Lamei Zou; Changfeng Li; Weidong Yang; Shiyang Zhou; Shiwei Nie

doi:10.1117/12.2539136

14 February 2020 Remote sensing image ship detection based on feature pyramid

Lamei Zou, Changfeng Li, Weidong Yang, Shiyang Zhou, Shiwei Nie

Proceedings Volume 11430, MIPPR 2019: Pattern Recognition and Computer Vision; 1143013 (2020) https://doi.org/10.1117/12.2539136
Event: Eleventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2019), 2019, Wuhan, China

Abstract

We present a two-stage method for remote sensing image ship detection. The proposed approach efficiently detects ships in remote sensing images. Firstly, a light-weight classification network is used to classify different regions. In second stage, we design a detection framework to detect ships in sub-images, which are considered to contain object in the first stage. To solve the scale problems in object detection, our detection network is built on feature pyramid network, but we explicitly assign object into corresponding feature maps based on size. In our proposed framework, instead of using anchors, we predict object center point and the offsets to bounding box. The experiment results show that our proposed method has a good performance in terms of speed and accuracy.

Citation Download Citation

Lamei Zou, Changfeng Li, Weidong Yang, Shiyang Zhou, and Shiwei Nie "Remote sensing image ship detection based on feature pyramid", Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 1143013 (14 February 2020); https://doi.org/10.1117/12.2539136

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