English

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

Computer Vision and Pattern Recognition 2020-07-06 v2

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.

Keywords

Cite

@article{arxiv.2006.10383,
  title  = {3D Pipe Network Reconstruction Based on Structure from Motion with Incremental Conic Shape Detection and Cylindrical Constraint},
  author = {Sho kagami and Hajime Taira and Naoyuki Miyashita and Akihiko Torii and Masatoshi Okutomi},
  journal= {arXiv preprint arXiv:2006.10383},
  year   = {2020}
}

Comments

This manuscript was accepted and presented in the 29th IEEE International Symposium on Industrial Electronics (ISIE2020)

R2 v1 2026-06-23T16:25:37.565Z