.png){kind=icon}
Return
Single-pass inline pipeline 3D reconstruction using depth camera array
.png){kind=icon}
OA
AI
DOI：10.1016/j.autcon.2022.104231.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
A novel inline inspection (ILI) approach using depth cameras array (DCA) is introduced to create high-fidelity, dense 3D pipeline models. A new camera calibration method is introduced to register the color and the depth information of the cameras into a unified pipe model. By incorporating the calibration outcomes into a robust camera motion estimation approach, dense and complete 3D pipe surface reconstruction is achieved by using only the inline image data collected by a self-powered ILI rover in a single pass through a straight pipeline. The outcomes of the laboratory experiments demonstrate one-millimeter geometrical accuracy and 0.1-pixel photometric accuracy. In the reconstructed model of a longer pipeline, the proposed method generates the dense 3D surface reconstruction model at the millimeter level accuracy with less than 0.5% distance error. The achieved performance highlights its potential as a useful tool for efficient in-line, non-destructive evaluation of pipeline assets.
Keywords:
ILI
Visual inspection
Pipeline
Depth camera array
Camera calibration
Robotic
Motion estimate
Dense point-cloud model
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
11.5
Papers:
6.3K
Citations:
4.2W
Organization
Cited Papers
Status and public perception of the ‘New Zealand flatworm’, Artioposthia triangulata (Dendy), in Northern Ireland.png)
PedobiologiaOAAI
PedobiologiaIF0
OAAIShareSaveTrinocular stereo system with object space oriented correlation for inner pipe inspectionMEASUREMENT
MEASUREMENTIF5.6
PREAI
ShareSaveStereo Vision Combined With Laser Profiling for Mapping of Pipeline Internal DefectsIEEE SENSORS JOURNAL
IEEE SENSORS JOURNALIF4.5
PREAI
ShareSaveShareSaveShareSave
View more