3D Reconstruction of Oil Refinery Buildings Using a Depth Camera


Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

We propose a method for fast three-dimensional reconstruction of oil refinery buildings and facilities using photography with the help of an unmanned aerial vehicle (drone) and a depth sensor for depth image classification. We propose two workflows for object reconstruction for different applications. To use the depth sensors, we have developed a method combining the Structure from Motion (SfM) method for determining the structure of an object from imaging of motion in passive vision mode and the Structural Light (LS) method or Time-of-Flight (ToF) method in active (illuminated) vision mode. With low costs, the SfM method combined with a depth sensor let us obtain images large-scale objects at high speed, where the number of calculations is significantly reduced, the efficiency of 3D reconstruction is improved, and the uncertainty in determining the object parameters is not more than a few centimeters.

About the authors

Shuaihao Li

School of Computer Science, Wuhan University

Email: chenmin@whu.edu.cn
China, Wuhan

Yanxiang He

School of Computer Science, Wuhan University

Email: chenmin@whu.edu.cn
China, Wuhan

Xinfeng Yang

School of Computer Science, Wuhan University

Email: chenmin@whu.edu.cn
China, Wuhan

Qianqian Li

School of Computer Science, Wuhan University

Email: chenmin@whu.edu.cn
China, Wuhan

Min Chen

School of Computer Science, Wuhan University

Author for correspondence.
Email: chenmin@whu.edu.cn
China, Wuhan

Supplementary files

Supplementary Files
Action
1. JATS XML

Copyright (c) 2018 Springer Science+Business Media, LLC, part of Springer Nature