Semantic Segmentation Based Building Extraction Method Using Multi-Source GIS Map Datasets and Satellite Imagery

Weijia Li, Conghui He, Jiarui Fang, Haohuan Fu; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2018, pp. 238-241

Abstract


This paper describes our proposed building extraction method in DeepGlobe - CVPR 2018 Satellite Challenge. We proposed a semantic segmentation and ensemble learning based building extraction method for high resolution satellite images. Several public GIS map datasets were utilized through combining with the multispectral WorldView-3 satellite image datasets for improving the building extraction results. Our proposed method achieves the overall prediction score of 0.701 on the test dataset in DeepGlobe Building Extraction Challenge.

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[bibtex]
@InProceedings{Li_2018_CVPR_Workshops,
author = {Li, Weijia and He, Conghui and Fang, Jiarui and Fu, Haohuan},
title = {Semantic Segmentation Based Building Extraction Method Using Multi-Source GIS Map Datasets and Satellite Imagery},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2018}
}