3D Point Cloud Vectorization for LiDAR City Models
This hands-on approach is standalone and covers the process of LiDAR Vectorization. We then focus on City Model Automatic Generation (LoD 0) in 5 main phases. We are going to code a solution with Python that takes a point cloud (.laz), and returns instantiated vectorized houses with both their 2D footprint and 3D LoD 0 Mesh Model.
This hands-on approach is standalone and covers the process of LiDAR City Model Automatic Generation (LoD 0) in 5 main phases. We are going to code a solution with Python that takes a point cloud (.laz), and returns instantiated vectorized houses with both their 2D footprint and 3D LoD 0 Mesh Model.
Vectorization Materials and 3D Tutorial Resources
🍇3D Dataset + Code: Google Drive Folder
📘Hands-on Guide: In Editorial Phase
My 3D Recommendation 🍉
Turning raster and 3D unstructured datasets (i.e.) point clouds into vectors is often an integral cog of systems in production. I would recommend following up the 3D Python Crash Course if you want to kickstart your journey by creating solutions to identified challenges, using only your computer and Python: 3D Python Crash Course
If you want to get a tad more toward application-first or depth-first approaches, I curated on this website several learning tracks and courses to help you along your journey. Feel free to follow the ones that best suit your need, and do not hesitate to reach out directly to me if you have any questions or if I can give you some advice on your current challenges!
Open-Access Knowledge
- Medium Tutorials and Articles: Standalone Guides and Tutorials on 3D Data Processing (5′ to 45′)
- Research Papers and Articles: Research Papers published as part of my public R&D work.
- Email Course: Access a 7-day E-Mail Course to Start your 3D Journey
- Youtube Education: Not articles, not research papers, open videos to learn everything around 3D.
3D Online Courses
- 3D Python Crash Course (Complete Standalone). 3D Coding with Python.
- 3D Photogrammetry Course (Complete Standalone): Open-Source 3D Reconstruction.
- 3D Point Cloud Course (Complete Standalone): Pragmatic, Complete, and Commercial Point Cloud Workflows.
- 3D Object Detection Course (3D Python Recommended): Practical 3D Object Detection with 3D Python.
3D Learning Tracks
- 3D Segmentation Deck: From Classical 3D Segmentation to 3D Deep Learning and Unsupervised Applications
- 3D Collector’s Pack: Complete Course Track to address both 3D Application and Code Layers.