Measurement Accuracy Assessment in 3D Models Derived from Drone Surveys

Engineering Surveying & Deformation Monitoring

Authors

First and Last Name	Academic degree	E-mail	Affiliation
Sonia Calluso	No	sonia.calluso [at] outlook.it	Freelance External Collaborator DICEAM - Department of Civil, Energy, Environment and Materials Engineering - Mediterranea University of Reggio Calabria (Italy) Reggio Calabria, Italy
Giuseppe Maria Meduri	No	ing.giuseppemariameduri [at] gmail.com	DICEAM - Department of Civil, Energy, Environment and Materials Engineering - Mediterranea University of Reggio Calabria (Italy) Reggio Calabria, Italy
Vincenzo Gullace	No	gllvcn77a15h558w [at] studenti.unirc.it	DICEAM - Department of Civil, Energy, Environment and Materials Engineering - Mediterranea University of Reggio Calabria (Italy) Reggio Calabria, Italy
Maurizio Manti	No	ing.manti5 [at] gmail.com	Freelance External Collaborator DICEAM - Department of Civil, Energy, Environment and Materials Engineering - Mediterranea University of Reggio Calabria (Italy) Reggio Calabria, Italy
Emanuela Genovese	No	emanuela.genovese [at] unirc.it	DICEAM - Department of Civil, Energy, Environment and Materials Engineering - Mediterranea University of Reggio Calabria (Italy) Reggio Calabria, Italy

I and my co-authors (if any) authorize the use of the Paper in accordance with the Creative Commons CC BY license

First published on this website: 27.08.2023 - 12:30

Abstract

Unmanned Aerial Vehicle (UAV) systems, or drones, have gained prominence in surveying due to their efficiency and accessibility advantages. Employed with computer vision algorithms, they reconstruct accurate 3D models, transforming data acquisition. Although commonplace for inspections, monitoring, and controls, their use in infrastructure measurements remains limited. This study addresses this gap, focusing on accuracy assessment. Assessing accuracy requires considering parameters during both survey and processing phases. This research aims to predict the accuracy of 3D reconstruction from UAV surveys using commercial software (Agisoft Metashape). By analyzing key parameters, we establish a relationship to anticipate survey accuracy based on predefined choices. This study advances UAV-based infrastructure measurement accuracy, offering insights for better decision-making and precision in the field.

Keywords

References

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