MODAM3: Modeling and Algorithms for the Localization, Characterization, and Identification of Objects in Massive, Multi-scale, and Temporal 3D Point Clouds

Objectives:
The MODAM3 project aims to develop new models and algorithms for the automatic localization, characterization, and identification of objects in massive, multi-scale, and temporal 3D point clouds generated from airborne LiDAR, photogrammetry, and 3D scanners. The targeted applications focus on the environment and coastal heritage, within an academic–industry consortium involving GREYC–M2C–NORM3D–ROBORATIVE.

Location: Image Team, GREYC UMR CNRS 6072

Supervisor:
A. Elmoataz, Professor at the University of Caen Normandy

Postdoctoral position duration: 12 to 24 months

Project Summary

LiDAR technologies, photogrammetry, and 3D scanners now make it possible to produce enormous volumes of data describing our cities, coastlines, infrastructure, and cultural heritage. However, automatically exploiting and analyzing these data remains a major challenge.
The ModAM³ project aims to develop a new generation of artificial intelligence methods for analyzing 3D data and automatically detecting objects and changes in the environments under study.
Within this project, GREYC proposes to introduce new multi-scale graph-based representations adapted to massive and temporal data. Data processing tasks, such as localization, classification, and object recognition, will be addressed through the development of novel fundamental methods for semi-supervised and unsupervised learning. These methods will be based on new classes of partial differential equations on graphs and new graph neural network models based on diffusion processes.
The developed algorithms will be applied to several application domains, particularly cultural heritage, with a focus on Pointe du Hoc, a major historical site of the Second World War.
GREYC already has expertise in 3D reconstruction and 3D printing for cultural heritage applications, with the aim of facilitating access to and work by researchers and conservators, as well as improving accessibility for visually impaired people.

Where to apply

E-mail: abderrahim.elmoataz-billah@unicaen.fr

Requirements

Research Field: Computer science

Education Level: PhD or equivalent

Skills/Qualifications

Applicants should hold a PhD in Computer Science, Signal and Image Processing, Computer Vision, Geomatics, or a related field, with skills in:

• Python and/or C++ programming;
• Image processing, 3D geometry, or computer vision;
• Processing and analysis of 3D data / point clouds.

Knowledge of libraries or tools such as PCL, Open3D, PDAL, and CloudCompare, as well as machine learning/deep learning methods applied to 3D data, will be considered an asset.

Additional Information

Selection process

Application
Please send your CV and cover letter to:
abderrahim.elmoataz-billah@unicaen.fr

Work Location(s)

Number of offers available: 1

Company/Institute: Université de Caen Normandie - GREYC research unit

Country: France

City: Caen

Postal Code: 14000

Street: Boulevard du Maréchal Juin

Contact

City: Caen

Website: http://www.unicaen.fr

Street: Esplanade de la Paix 14032 CAEN CEDEX

Postal Code: CS 14032

E-Mail: abderrahim.elmoataz-billah@unicaen.fr