C++ internship: 3d point cloud processing in Unreal Engine (job offer closed)
6 months – Master 2 Internship.
STORM research group, CNRS, IRIT, Toulouse.
Contact: nicolas.mellado AT irit.fr
Context
3D point clouds are now ubiquitous thanks to the development of surface acquisition technologies (e.g. LiDAR, stereovision, photogrammetry). Modern acquisition techniques produce point clouds mades of billions of samples. This massive amount of data complexifies every operation: visualization, processing, storage, sharing… In this context, working with point clouds require high-end software providing fast, efficient and robust tools.
Point clouds are not the unique representation for 3d content: movies, games, augmented reality software (among other) also require to represent, process and visualize 3d information efficiently and at large scale. The goal of this project is to study how to combine industry-grade general-purpose 3d software with point-based geometry processing libraries, in order to develop the next generation of point cloud editing and processing tools.
Project description
The main objective of this internship is to develop a proof of concept demonstrating how 3d point clouds can be visualized and processed in the Unreal Engine (UE).
The intern will be in charge of designing and developing an application based on UE 5.1, allowing to load, render, interact and process acquired 3d point clouds. Point cloud processing will be delegated to the PONCA library (see link section below).
Skills
- Knowledge in Computer Graphics and/or Computer Vision
- Strong programming skills (modern C++)
- Bonus:
- Experience in 3d point cloud analysis/processing
- Experience in development with Unreal Engine
Links
Unreal Engine LiDAR Point Cloud plugin
https://docs.unrealengine.com/5.0/en-US/lidar-point-cloud-plugin-for-unreal-engine/
PONCA: POiNt Cloud Analysis library
Ponca is a header only library coded in C++, and compatible with CUDA. It is maintained by researchers in Computer Graphics, and released under the MPL license. Source code is available at: https://github.com/poncateam/ponca