2134/9816734.v1
Luigi Parente
Luigi
Parente
Jim Chandler
Jim
Chandler
Neil Dixon
Neil
Dixon
Optimising the quality of an SfM‐MVS slope monitoring system using fixed cameras
Loughborough University
2019
Geological & Geomatics Engineering
Geomatic Engineering
Calibration
Change detection
Monitoring
Network geometry
Photogrammetry
Structure-from-motion (SfM)
Artificial Intelligence and Image Processing
2019-09-16 09:40:32
Journal contribution
https://repository.lboro.ac.uk/articles/journal_contribution/Optimising_the_quality_of_an_SfM_MVS_slope_monitoring_system_using_fixed_cameras/9816734
The quality of 3D scene reconstruction and monitoring through structurefrom-motion multiview stereo (SfM-MVS) depends on critical key factors, including
camera calibration and image network geometry. The goal of this paper is to
examine the monitoring ability of an SfM-MVS workflow based on four or more
ground-based digital single-lens reflex (DSLR) cameras and to estimate differences
when adopting both fixed and variable camera positions and orientations. This
was achieved by conducting work on a scaled laboratory testfield and a sea cliff.
Tests demonstrate that a monitoring system using just four fixed cameras can
achieve valuable monitoring capabilities and tolerate imperfections in the camera
calibration. Furthermore, such a configuration can achieve accuracies comparable
to terrestrial laser scanning (TLS) and drone-based photogrammetry. The study
demonstrates that minimising registration errors between point clouds is critical.
The “registration SIFT” approach could resolve such problems.