| Autor: |
Joel Mohren, Maximilian Schulze |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
MethodsX, Vol 12, Iss , Pp 102679- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2215-0161 |
| DOI: |
10.1016/j.mex.2024.102679 |
| Popis: |
The U.S. Geological Survey (USGS) has published a guideline to improve the quality of digital photogrammetric reconstructions created with the widely used Agisoft Metashape Professional software. The suggested workflows aim at filtering out low-quality tie points from the tie point cloud to optimize the camera model. However, the optimization procedure relies on an iteratively performed trial-and-error approach. If manually performed, the time expenditure required from the operator can be significant and the optimization process can be affected by the degree of diligence that is applied.To minimize the time expenditure and attentiveness required from the operator and to provide a framework for an improved reproducibility of camera model optimization workflows, we present here a python script serving as an extension for Agisoft Metashape Professional (tested on version 2.1.0) that automatizes the iterative point filtering procedure proposed by the USGS. As a result, the entire processing cycle can be performed largely unattended. • A graphical user interface allows to individually adjust important camera model optimization parameters. • Main tie point cloud quality measures can be directly assessed. • The reproducibility of the automated camera model optimization as tested in this study generally is above 99%. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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