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3D Pipe Network Reconstruction Based on Structure from Motion with Incremental Conic Shape Detection and Cylindrical Constraint

Authors :
kagami, Sho
Taira, Hajime
Miyashita, Naoyuki
Torii, Akihiko
Okutomi, Masatoshi
Publication Year :
2020

Abstract

Pipe inspection is a critical task for many industries and infrastructure of a city. The 3D information of a pipe can be used for revealing the deformation of the pipe surface and position of the camera during the inspection. In this paper, we propose a 3D pipe reconstruction system using sequential images captured by a monocular endoscopic camera. Our work extends a state-of-the-art incremental Structure-from-Motion (SfM) method to incorporate prior constraints given by the target shape into bundle adjustment (BA). Using this constraint, we can minimize the scale-drift that is the general problem in SfM. Moreover, our method can reconstruct a pipe network composed of multiple parts including straight pipes, elbows, and tees. In the experiments, we show that the proposed system enables more accurate and robust pipe mapping from a monocular camera in comparison with existing state-of-the-art methods.<br />Comment: This manuscript was accepted and presented in the 29th IEEE International Symposium on Industrial Electronics (ISIE2020)

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2006.10383
Document Type :
Working Paper