The best way to master 3D point cloud processing.
by Florent Poux, PhD
From Beginner to Master with only one course
Embarking on the 3D Point Cloud Journey will give you lifetime access to a complete, easy-to-follow course with 40 lessons.
Want to see what’s included? Check out the video down below:
Each chapter begins with a starter folder to download.
Then, simply follow the lessons!
After each video, you get a pdf handout with the key takeaways.
Plus, you can slow down or speed up the videos!
🎓 What will you learn?
Point Cloud Processing Course Syllabus
Main objectives
- Master the context of point cloud datasets (platforms, domains, software)
- Develop ETL (Edit Transform Load) for various point cloud file formats (ASCII and BINARY)
- Learn how to switch between 3D data representations (Mesh, Point Cloud, Volumetric)
- Create a full data pre-processing workflow (incl. sampling strategies, data cleaning, transformation and reduction)
Additional content and resources
Additional content and resources- Access to Point Cloud Datasets (folder)
- Access to Mesh Datasets (folder)
- Access to CloudCompare projects (folder, .bin)
- Article on 3D Data Representation (.pdf)
Main objectives
- Derive valuable information from point cloud datasets
- Develop various neighborhood selection methods for optimal local/global description
- Apply PCA to extract meaaningful features for point cloud analysis
- Master the creation of point normals and their typology
- Select feature sets for specific applications (analysis vs classification)
- Master coarse-to-fine registration methodologies
- Increase your focus on the ICP (Iterative Closest Point) algorithm
Additional content and resources
Additional content and resources- Point Cloud Datasets (folder)
- CloudCompare projects (folder, .bin)
- Coarse registration methodologies (.pdf)
- Fine registration methodologies (.pdf)
Main objectives
- Learn and apply several segmentation workflows (+ Euclidean Clulstering)
- Engineer new distinctive features (E.g. Difference of Normals)
- Develop a Classification (i.e. Semantic segmentation) evaluation and deployement system
- Apply best-in-class Machine Learning classifiers for point-based or object-based classification
- Fast initation to Python and Google Colab scripting
Additional content and resources
Additional content and resources- Point Cloud Datasets (folder)
- CloudCompare Projects (folder, .bin)
- Access to Google Colab Machine Learning Classification (.ipy)
- Article scientifique: Self-Learning (.pdf)
- Article scientifique: Semantic-segmentation (.pdf)
Main objectives
- Apply 3 point cloud comparison strategies: Cloud-to-cloud, Cloud-to-mesh, Cloud-to-HF
- Put a control system in place to produce robust quality reports
- Learn and apply the fundamentals of statistical analysis to describe the produced graphics
- Create stunning 3D renderings (video and still)
- Deliver point cloud as a product through produced 3D desktop and/or web applications
Additional content and resources
Additional content and resources- Point Cloud Datasets (folder)
- CloudCompare Projects (folder, .bin)
- Tutorial: Potree Web and Desktop (update rolling)
- Tutorial: Setting up web servers (update rolling)
Main objectives
- Create and use 3D Data structures (kd-tree, octree, voxels, …)
- Parse point cloud data set in specific structures for efficient point cloud processing
- Learn & Apply 3 different meshing approaches (Ball-pivoting, Poisson, Delaunay)
- Optimize point cloud to mesh workflows (tri-count, topology …)
Additional content and resources
Additional content and resources- Point Cloud Datasets (folder)
- Meshes Datasets (folder)
- CloudCompare Projects (folder, .bin)
- Article on 3D data representations (.pdf)
- Tutorial: How to use MeshLab Software
- Article on 3D point cloud modelling (.pdf)
Main objectives
- Learn and Code with Python for 3D Data
- Combine Python with the Command Line to access advanced CloudCompare functionnalities
- Develop a modular program that can address the 5 key processing steps of point cloud data
- Deploy a program to automatically generate 3D meshes from massive point cloud data
Additional content and resources
Additional content and resources- Article: Discover 3D Point Cloud Processing with Python (.pdf)
- Article: Generate 3D Meshes with Python (.pdf)
- Article: Generate 3D Meshes with Python (.pdf)
- Tutorial: Anaconda software and python environment
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🦚 Get the best learning experience from Academia & Industry
Meet Dr. Florent Poux
Florent Poux is a Renown Scientist specializing in 3D Data Processing. He has published award-winning research articles on point clouds, 3D segmentation, and AI, and worked on many projects for renowned clients to create interactive 3D experiences accessible to everyone from their browser.
Florent has been teaching 3D Geodata Science and Machine Learning in various Universities for more than 10 years, making him a pedagogical trainer, alternating theory and practice.
A portion of Point Cloud Process. profits will be donated to young companies that want to grow and 3D researchers that need funding to deliver the next big thing. You will therefore participate directly in the success of others.
🧙♂️ Become a 3D Expert before the niche gets crowded!
Satisfaction Guarantee
I stand behind the quality of this course. If you are not happy with it, I am not happy with it. 14-Days Money-Back Guarantee.
Course Director
A. Prof. Florent Poux
🍇Point Cloud Processor
- 5 Modules, 40 Video Training
- Copy-Paste Methods + Workflows
- All-Included (Code, Data, Models, Handouts)
- Commercial License Possibility
- Python Automation Bonuses
- Ph.D. level support (5/7 days)
- Premium Community Access
- Lifetime updates (monthly)
- Lifetime access
🎁 Exclusive for first 250 innovators (3 left)
“The ultimate course for engineers to develop automation systems for 3D point clouds: understand, build and deploy fast”
🦄 They Trust and Learn with the 3D Academy
Is Point Cloud Processing the right 3D course for you?
The 3D Course is focused on results
Who?
You want to develop a complete set of 3D skills, with a focus on automation. The program is time-efficient, but demands motivated individuals.
What?
At the end of the course, you can start a 3D Point Cloud Processing Service (through the Web, or your own Activity)
How?
Point Cloud Processor is a gas pedal, but it is still a step-by-step enrichment process. You're taken through a structured course that makes everything easy and efficient.
Beyond?
Scale your practice and get started with full 3D automation. You can optionnally book a private session or a mentorship program for a very advanced training.
Fast results
There is no faster way to be recognized and master technology than learning from professionals.
Frictionless learning
With years of R&D, benefit from engineered courses designed for time-efficient learning.
Accessible Premium
Premium should not be accessible only to the wealthy, but to the willing minds that take action.
Don't Get Left Behind by the Research on 3D Data Processing
- 9+ hours of exclusivevideo in 5+1 bonus modules
- Full expert point cloud processing workflow
- Pass All-Included: Supporting tutorials (.pdf), articles (.pdf), Software, Python Scripts, Colab Notebooks, Datasets ...
- Engineered & certifiable by recognized University teacher
- 3 Bonus skills on 3D Automation programming with Python
- Lifetime access including future upgrades & updates
- Private forum for members only and mentoring possibilities
What happens upon subscription?
Forever. It is lifetime access. No subscription. No hidden fees. Everything is yours.
The complete training represents more than 9 hours of explanatory video. At the beginning of each module, you will have a short theoretical part in order to start from scratch. Then the rest of the entire training will include actions to be implemented immediately to get results.
If you binge-watch the course, account for 9 hours. But add on top the time to replicate and infuse the knowledge.
Nope. This is free-form: you go at your own pace, following your own path. But of course, it is recommended to follow the linear progression.
The advantage with online training is that you can access all the videos without having to go anywhere, from the comfort of your own home.
Florent offers individual online coaching, with single or multiple sessions. This is why it is financially advantageous to follow our online programs.
Whether it is for the structure of our advice in a condensed and precise way, the discount on the price, the unlimited access that allows you to come back at any time to each of the videos, it is more advantageous to train remotely.
If you are in a situation where you have major financial difficulties as a student, you can apply for a scholarship by reaching out directly via mail.
I have a limited number of seats that I renew each year for motivated applicants. I always try my best to support the future bright minds of today and tomorrow.
If upon completion of the course, you believe you did not got any added value, I will make sure you are fully refunded.
Yes! Double Yes! Triple Yes! Wether you are a land surveyor, working on autonomous driving, forestry or GIS, this course is tailored for you. You have both the knowledge, the demonstration, and also use cases for your specific application.