Florent Poux main focus is on point cloud analysis from Terrestrial Laser scanner, MLS, LiDAR and SFM / photogrammetric reconstructions. He works to make this 3D data accessible easily, securely and making classification a smart tool for many industries from surveying to autonomous driving.
Scale AI releases a new open-source dataset for both academic and commercial use, and accelerate the growth of Autonomous Driving research. For self-driving car applications,… Read More »Free LiDAR datasets for self-driving cars AI applications
A visual guide to help choose data representations among 3D point clouds, meshes, parametric models, depth-maps, RGB-D, multi-view images, voxels… The 3D datasets in our… Read More »How to represent 3D Data?
In this article, I will give you my 3D surface reconstruction process for quickly creating a mesh from point clouds with python. You will be… Read More »5-Step Guide to generate 3D meshes from point clouds with Python
Discrete spatial datasets known as point clouds often lay the groundwork for decision-making applications. But can they become the next big thing? I am a… Read More »The Future of 3D Point Clouds: a new perspective
The surveying intensive practical project took place this year in the castle of Jehay. Here are the 3D members of this very motivated team of… Read More »2017M1 3D Students
Due to the rapid development of surveying and reality capture technologies, the acquisition of point clouds continues to become easier and faster while incurring lower… Read More »Data Acquisition
The large datasets that point clouds constitute cannot directly fit in the main memory, demanding a new structure to exploit through a Database Management System… Read More »Data Preparation
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