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.