Roving Multiple Camera Array with Structure-from-Motion for Coastal Monitoring

• Published in: Journal of marine science and engineering Vol. 11; no. 3; p. 591
• Main Authors: Godfrey, Samantha, Cooper, James R., Plater, Andrew J.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.03.2023
• Subjects: Arrays; camera array; camera rig; Cameras; coastal monitoring; coastal recession; Coastal structures; Computation; Data acquisition; Deformation; Densification; Dimensions; Environmental monitoring; Error reduction; Estimates; Estuaries; Global positioning systems; GPS; Image acquisition; Lasers; Monitoring; Parameters; Process parameters; Reconstruction; SfM-MVS processing parameters; Software; structure-from-motion photogrammetry; Traction; Unmanned aerial vehicles; United Kingdom; United Kingdom > UK; England
• ISSN: 2077-1312; 2077-1312
• DOI: 10.3390/jmse11030591

Regular monitoring is essential for vulnerable coastal locations such as areas of landward retreat. However, for coastal practitioners, surveying is limited by budget, specialist personnel/equipment and weather. In combination structure-from-motion and multi-view stereo (SfM-MVS) has helped to improve accessibility to topographic data acquisition. Pole-mounted cameras with SfM-MVS have gained traction but to guarantee coverage and reconstruction quality, greater understanding of camera position and interaction is required. This study uses a multi-camera array for image acquisition and reviews processing procedures in Agisoft Photoscan (Metashape). The camera rig was deployed at three sites and results were verified against a terrestrial laser scanner (TLS) and independent precision estimates. The multi-camera approach provided effective image acquisition ~11 times faster than the TLS. Reconstruction quality equalled (>92% similarity) the TLS, subject to processing parameters. A change in the image alignment parameter demonstrated a significant influence on deformation, reducing reprojection error by~94%. A lower densification parameter (‘High’) offered results ~4.39% dissimilar from the TLS at 1/8th of the processing time of other parameters. Independent precision estimates were <8.2 mm for x, y and z dimensions. These findings illustrate the potential of multi-camera systems and the influence of processing on point cloud quality and computation time.