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Achieving Tiered Model Quality in 3D Structure from Motion Models Using a Multi-Scale View-Planning Algorithm for

Trent J Okeson1, Benjamin J Barrett2, Samuel Arce3

  • 1Department of Chemical Engineering, Ira A. Fulton College of Engineering and Technology, Brigham Young University, 350 Clyde Building, Provo, UT 84602, USA. okesontj@byu.net.

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Summary

This study introduces a new multi-scale view-planning algorithm for automated infrastructure inspection using unmanned aircraft systems (UAS). This approach significantly reduces flight time and data processing by prioritizing inspection areas, achieving high accuracy with fewer images.

Keywords:
Multi-Scaleautomated inspectiondam inspectionstructure from motionunmanned aerial vehiclesview-planning

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Area of Science:

  • Robotics and Automation
  • Geospatial Engineering
  • Computer Vision

Background:

  • Industrial inspection demands efficient data collection to minimize computational and human processing loads.
  • Structure from Motion (SfM) based infrastructure modeling requires optimized image acquisition strategies.
  • Current view-planning methods for SfM often lack multi-scale capabilities for targeted inspection.

Purpose of the Study:

  • To investigate the viability of automated, targeted, multi-scale image acquisition for SfM-based infrastructure modeling.
  • To develop and validate a novel multi-scale view-planning algorithm for unmanned aircraft systems (UAS).
  • To optimize data collection for industrial inspection, reducing processing demands while maintaining model accuracy.

Main Methods:

  • Extended traditional SfM view-planning to a multi-scale approach, incorporating high, medium, and low priority regions.
  • Utilized unmanned aerial vehicles (UAVs) for automated flight path planning and image acquisition.
  • Validated the algorithm through a field test case at the Tibble Fork Dam, Utah.

Main Results:

  • Achieved high-accuracy modeling of infrastructure using less than 25% of the photos required for full-scale high-priority modeling.
  • Demonstrated approximately 75% reduction in flight time and model processing load.
  • Observed stepped improvements in model clarity and SfM reconstruction integrity based on priority levels, with finer features accurately modeled in high-priority regions.

Conclusions:

  • The developed multi-scale view-planning algorithm enables efficient and accurate automated infrastructure inspection using UAVs.
  • The method significantly reduces data acquisition and processing requirements, making it suitable for industrial applications.
  • The approach shows potential for extension to other remote sensing modalities like aerial LiDAR.