Context

CARS allows 3D scenes reconstruction by photogrammetry. The tool will be integrated into the ground segment of the CO3D mission. The present study aims to improve the denoising of point clouds produced by CARS for the reconstruction of 3D scenes. A first study was carried out by CS in 2022 to improve the method for denoising point clouds in epipolar geometry. This R&T is the continuation of this study, it aims to pursue investigations for improvement and industrialize them via a plugin in CARS.

CS Group responsabilities for Point cloud clearing in epipolar geometry using trusted intervals are as follows:

Research and software development

Main Picture

The features are as follows:

CARS allows 3D reconstruction by photogrammetry, it will be integrated into the ground segment of the CO3D mission.
This R&T takes the results of the 2022 study conducted by CS and attempts to improve the methode for denoising point clouds generated by CARS for 3D reconstruction.
The idea is to work in epipolar geometry.
The goal is to remove noise while preserving important details, to improve the MNS producted by CARS.
This study integrates the development of a plugin in CARS.

Project implementation

The project objectives are as follows:

Improving CARS point cloud denoising methods
Improving CARS output MNS
3D scene reconstruction by photogrammetry

The processes for carrying out the project are:

Agile

Technical characteristics

The solution key points are as follows:

Gitlab

The main technologies used in this project are:

Domain	Technology(ies)
Operating System(s)	Linux
Programming language(s)	Python
Production software (IDE, DEVOPS etc.)	Git, CARS, SLURP