Version 1
: Received: 11 October 2024 / Approved: 11 October 2024 / Online: 11 October 2024 (14:16:48 CEST)
How to cite:
Perfetti, L.; Bruno, N.; Roncella, R. Multi-Camera Rig and Spherical Camera Assessment for Indoor Surveys in Complex Spaces. Preprints2024, 2024100939. https://doi.org/10.20944/preprints202410.0939.v1
Perfetti, L.; Bruno, N.; Roncella, R. Multi-Camera Rig and Spherical Camera Assessment for Indoor Surveys in Complex Spaces. Preprints 2024, 2024100939. https://doi.org/10.20944/preprints202410.0939.v1
Perfetti, L.; Bruno, N.; Roncella, R. Multi-Camera Rig and Spherical Camera Assessment for Indoor Surveys in Complex Spaces. Preprints2024, 2024100939. https://doi.org/10.20944/preprints202410.0939.v1
APA Style
Perfetti, L., Bruno, N., & Roncella, R. (2024). Multi-Camera Rig and Spherical Camera Assessment for Indoor Surveys in Complex Spaces. Preprints. https://doi.org/10.20944/preprints202410.0939.v1
Chicago/Turabian Style
Perfetti, L., Nazarena Bruno and Riccardo Roncella. 2024 "Multi-Camera Rig and Spherical Camera Assessment for Indoor Surveys in Complex Spaces" Preprints. https://doi.org/10.20944/preprints202410.0939.v1
Abstract
This study compares the photogrammetric performance of three multi-camera systems—two spherical cameras (INSTA 360 Pro2 and MG1) and one multi-camera rig (Ant3D)—to evaluate their accuracy and precision in confined environments. These systems are particularly suited for indoor surveys, such as narrow spaces, where traditional methods face limitations. The instruments were tested for the survey of a narrow spiral staircase within Milan Cathedral and the results were analyzed based on different processing strategies, including different relative constraints between sensors, various calibration sets for distortion parameters, interior orientation (IO), and relative orientation (RO), as well as two different ground control solutions. The study also included a repeatability test. The findings showed that, with appropriate ground control, all systems achieved the target accuracy of 1 cm. In partially unconstrained scenarios, instead, the drift errors ranged between 5 and 10 cm. Performance varied depending on the processing pipelines, but the results suggest that imposing a multi-camera constraint between sensors and estimating both IO and RO parameters during the Bundle Block Adjustment yields the best outcomes. In less stable environments, it might be preferable to pre-calibrate and fix the IO parameters.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
