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

arXiv: https://arxiv.org/abs/2006.10383 · HTML: https://mlsanity.com/paper/2006.10383/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jun 2020.

## Built on by (most cited first, 2 of 2)

- [VIO-Aided Structure from Motion Under Challenging Environments](https://mlsanity.com/paper/2101.09657/) (2021)
- [Video-Based Camera Localization Using Anchor View Detection and Recursive 3D Reconstruction](https://mlsanity.com/paper/2107.03068/) (2021)

## Abstract (arXiv)

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.