Summer school on Point clouds and change detection in the Geosciences https://clouds2022.sciencesconf.org/
- Dimitri Lague dimitri.lague@univ-rennes1.fr
- Paul Leroy paul.leroy@univ-rennes1.fr
- Aljoscha Rheinwalt aljoscha.rheinwalt@uni-potsdam.de
- Bodo Bookhagen bodo.bookhagen@uni-potsdam.de
This github archive contains Python Codes, Jupyter Notebooks, and links to MP4 recordings.
- Basic Concepts of Lidar: [YouTube] [MP4 higher resolution]
- Structure from Motion Introduction: [YouTube] [MP4 higher resolution]
Installation of a Python environment with Open3D is described in the PDF. This assumes you have worked with Python before.
Visualization of LAZ and LAS files in Open3D and some applications showing 3D point cloud density calculations in a Jupyter Notebook.
- Jupyter Notebook: PointCloud_Visualization_with_Open3D.ipynb
- MP4 Recording of Jupyter Notebook walk through: [YouTube] [MP4 higher resolution]
- Example Dataset used in Jupyter Notebook: ALS data of Campus Golm link
Several short tutorial about point-cloud alignment methods and their applications.
- Jupyter Notebook Introduction to Distance Metrics between point clouds Distance_metrics_between_pointclouds.ipynb
- MP4 Recording of Jupyter Notebook Introduction to Distance Metrics between point clouds walk through: [YouTube] [MP4 higher resolution]
- Jupyter Notebook ICP with SVD for a Gaussian Hill ICP_SVD_Gaussian_hill.ipynb
- MP4 recording of Jupyter Notebook ICP with SVD for a Gaussian Hill [YouTube] [MP4 higher resolution]
- Jupyter Notebook Global and Fine Registration ICP_Registration_ALS_UAV.ipynb
- MP4 recording of Jupyter Notebook Global and Fine Registration walk through: [YouTube] [MP4 higher resolution]
- Example Dataset (used in Notebook Global and Fine Registration): ALS data of Campus Golm link
- Example Dataset (used in Notebook Global and Fine Registration): UAV data of Campus Golm link