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Towards Automated Measurement of As-Built Components Using Computer Vision.

Husein Perez1, Joseph H M Tah1

  • 1Oxford Institute for Sustainable Development, School of the Built Environment, Oxford Brookes University, Oxford OX3 0BP, UK.

Sensors (Basel, Switzerland)
|August 26, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces an automated computer vision pipeline for measuring construction components from a single image. This innovation simplifies progress monitoring and enhances accuracy in construction projects.

Keywords:
automated measurementcomputer visionmachine learning

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Area of Science:

  • Construction Engineering and Management
  • Computer Vision
  • Artificial Intelligence

Background:

  • Accurate construction progress monitoring is essential for project adherence to timelines and budgets.
  • Current methods like 3D laser scanning and photogrammetry are complex and challenging to deploy on dynamic sites.
  • Frequent physical site observations are needed to verify construction progress.

Purpose of the Study:

  • To develop an automated pipeline for measuring as-built components using AI and computer vision.
  • To overcome the limitations of existing 3D measurement techniques in construction environments.
  • To enable accurate size measurement of construction elements from a single image.

Main Methods:

  • Proposed a novel pipeline utilizing artificial intelligence and computer vision.
  • Employed a stereo camera system to capture a single image for data acquisition.
  • Developed a method for automated measurement of as-built components like concrete walls and columns.

Main Results:

  • Successfully demonstrated the automated measurement of concrete wall and column sizes.
  • Achieved accurate geometric property ascertainment using a single image and target.
  • Validated a fully automated computer vision-based measurement method.

Conclusions:

  • The proposed pipeline offers a simplified and automated approach to measuring as-built components.
  • This method is suitable for measuring components in built assets and has potential for progress monitoring.
  • Integration with Building Information Modelling (BIM) applications can further enhance construction project management.