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VoxFall (Volumetric rockFall) is an open-source software for automatical detection and quantification of rockfall events as discrete blocks directly between two 3D models.
VoxFall does not rely on any distance computation between two models while is free from scale parameters associated to normals, spatial clustering, and cluster shape reconstruction.
The method treats the two input models as a single scene and applies two steps: 1) fitting an occupancy voxel grid of a resolution defined by the registration error; 2) empty space clustering and volume computation based on voxel adjacency.
VoxFall is freely available in 2 ways:
- As a CloudCompare plugin (Windows and Linux)
- As a Python package (In Windows, Linux and macOS)
VoxFall is available in Windows as a plugin in CloudCompare (2.14+)
Simply install the latest version of CloudCompare and in the menu bar navigate to:
Plugins → VoxFall
Running the plugin will open VoxFall's graphical user interface (GUI).
For detailed instructions on how to use the VoxFall plugin, please refer to the official documentation on the CloudCompare wiki.
⏳ Coming Soon - The Python package is currently under development and will be available shortly. Stay tuned for updates!
If you use VoxFall in your research, please cite the following paper:
Farmakis, I., Guccione, D. E., Thoeni, K., & Giacomini, A. (2025). VoxFall: Non-parametric volumetric change detection for rockfalls. Engineering Geology, 352, 108045. https://doi.org/10.1016/j.enggeo.2025.108045
@article{Farmakis2025,
author = {Farmakis, Ioannis and Guccione, Davide Ettore and Thoeni, Klaus and Giacomini, Anna},
title = {VoxFall: Non-parametric volumetric change detection for rockfalls},
journal = {Engineering Geology},
volume = {352},
year = {2025},
pages = {108045},
issn = {0013-7952},
doi = {10.1016/j.enggeo.2025.108045},
url = {https://www.sciencedirect.com/science/article/pii/S0013795225001413}
}Farmakis, Ioannis, Davide Ettore Guccione, Klaus Thoeni, and Anna Giacomini. "VoxFall: Non-parametric volumetric change detection for rockfalls." Engineering Geology 352 (2025): 108045. https://doi.org/10.1016/j.enggeo.2025.108045
Thank you for citing VoxFall in your work! Your citations help to support the continued development and maintenance of this software.
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VoxFall has been developed at the Research Centre for Geotechnical Science and Engineering of The University of Newcastle (Australia). Funding provided by the Australian Research Council (DP210101122): 'Efficient geotechnical risk management of rock cliffs' and the Australian Coal Association Research Program (ACARP C33040): 'Application and Validation of Machine Learning for Rockfall Analysis' |