Full text in English: https://www.umr-lastig.fr/vgouet/News/annonce_these_PlaceReco3D_2022-EN.pdf  

Full text in French: https://www.umr-lastig.fr/vgouet/News/annonce_these_PlaceReco3D_2022-FR.pdf  

The thesis project focuses on 3D point cloud based large-scale place recognition, with the application of geolocation of 3D image data. Without any extra information of the initial position, geolocalazing image content relies on the indexing and retrieval of content similarities in a geolocalized reference. This thesis proposes to study this type of approach by exploiting 3D maps based on acquisition campaigns (in particular LiDAR) that are becoming mainstream thanks to high quality geometry reconstruction which makes them attractive, but also complex to handle given their volume and diversity. Please consult the full text in PDF for the description of the subject thesis.

The fields of application of place recognition from images are numerous, we will deal here with the case of the geolocation of amateur video sequences as a certification tool for the prevention against fake news. Massively spread on social networks and on the web, amateur videos relaying information or an event are now very important, with among them content that is fake news, i.e. taken outside of its original context, to express bad or false information. To fight against this form of misinformation, several media, such as the French public television channel “France TV”, have set up a fact checking unit  of images and videos which analyzes, verifies and certifies these streams. This complex work is done by hand and would benefit from being automated by using artificial intelligence tools. The verification of geolocation was recognized as essential to best explain what is happening. It is in this collaborative context between IGN and France TV that we focus on this geolocation criterion with the desire to exploit the best georeferencing repositories of today to offer automatic large-scale geolocation solutions, which can, among other things, contribute to the fact checking of visual information.

Bac+5 in computer science, applied mathematics or geomatics (master or engineering school). A good background in machine learning is required, and a knowledge on 3D computer vision or image indexing will be appreciated. The successful candidate must have good programming skills (Python, C/C++). Although fluency in French is not required, fluency in English is necessary. Curiosity, open-mindedness, creativity, perseverance and the ability to work in a team are also key personal skills in demand.

* Start: last quarter of 2022

* Place: the thesis will be carried out in Paris area at the LaSTIG laboratory, located in Saint-Mandé (73 avenue de Paris, Saint-Mandé metro, line 1) in the premises of the IGN. The doctoral student will be attached to the MSTIC Doctoral School (ED 532).

The French mapping agency IGN (National Institute for Geographic and Forest Information) is a public administrative establishment attached to the French Ministry of Ecological Transition; it is the national reference operator for mapping the French territory. The LaSTIG  Laboratory in Sciences and Technologies of Geographic Information for the smart city and sustainable territories, is a joint research unit attached to the Gustave Eiffel University, the IGN and the School of Engineering of the city of Paris (EIVP). It is a unique research structure in France and even in Europe, bringing together around 80 researchers, who cover the entire life cycle of geographic or spatial data, from its acquisition to its visualization, including its modeling, integration and analysis; among them about thirty researchers work in image analysis, computer vision, machine learning, photogrammetry and remote sensing. LaSTIG researchers can be involved in the teaching activities of the IGN engineering school, the ENSG (Ecole Nationale des Sciences Géographiques), which offers access to undergraduate and graduate students with excellent quality in fields related to geographic information sciences: geodesy, photogrammetry, computer vision, remote sensing, spatial analysis, cartography, etc.

Before March 28, 2022, please send both contacts in a single PDF file the following documents:

- A detailed CV

- A topic-focused cover letter

- Grades and ranks over the last 3 years of study

- The contact details of 2 referents who can recommend you

- Laurent Caraffa – [log in to unmask], Researcher at LaSTIG (thesis supervisor), IGN, Gustave Eiffel University

- Valérie Gouet-Brunet – [log in to unmask], Research director at LaSTIG (director of the thesis), IGN, Gustave Eiffel University