Reconstruction of remote sensing image building contour based on end-to-end stacked hourglass network

doi:10.13474/j.cnki.11-2246.2022.0143

Abstract

Abstract: Considering the problem that how to reconstruct building contour in an end-to-end trainable way, a method of building contour reconstruction based on end-to-end and multi-residual module stacked hourglass network is proposed. Firstly, the multi-residual module stacked hourglass network is used to extract features of buildings' corners and edges. Secondly, the corners detection module is used to match the relative positions of the corresponding corners to obtain candidate corners, and then the candidate corners are sampled by line sampling module to generate candidate contour lines. Finally, the line verification module used candidate contour lines and feature map obtained by stacked hourglass network verify whether each line segment is a building contour, so as to obtain the result of building contour reconstruction. Experimental results show that on SpaceNet building data set, this method can detect the corners and edges of buildings, and effectively reconstruct the building contour in an end-to-end trainable way.

Key words: building contour reconstruction, stacked hourglass network, residual module, corner detection, line segment sampling

CLC Number:

P237

ZHANG Xingyi, LI Jiatian, YANG Ruchun, LU Dajin, ZHANG Zelong, YANG Chao. Reconstruction of remote sensing image building contour based on end-to-end stacked hourglass network[J]. Bulletin of Surveying and Mapping, 2022, 0(5): 67-73.

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