The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLIII-B2-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 817–823, 2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 817–823, 2021

  28 Jun 2021

28 Jun 2021


P.-M. Brunet1, P. Lassalle1, S. Baillarin1, B. Vallet2, A. Le Bris2, G. Romeyer2, G. Le Besnerais3, F. Weissgerber3, G. Foulon3, V. Gaudissart4, C. Triquet4, M. Darques4, G. Souille4, L. Gabet5, C. Ferrero6, T.-L. Huynh7, and E. Lavergne8 P.-M. Brunet et al.
  • 1Centre National d'Etudes Spatiales, Toulouse, France
  • 2IGN, Paris, France
  • 3ONERA, Paris, France
  • 4CS-SI, Toulouse, France
  • 5AIRBUS DS Intelligence, Toulouse, France
  • 6GEOSAT, Bordeaux, France
  • 7QuantCube, Paris, France
  • 8CLS, Toulouse, France

Keywords: Data processing, Photogrammetry, 3D, Semantic segmentation, Big Data, Platform

Abstract. The availability of 3D Geospatial information is a key issue for many expanding sectors such as autonomous vehicles, business intelligence and urban planning. Its production is now possible thanks to the abundance of available data (Earth observation satellite constellations, insitu data, …) but manual interventions are still needed to guarantee a high level of quality, which prevents mass production. New artificial intelligence and big data technologies adapted to 3D imagery can help to remove these obstacles. The AI4GEO project aims at developing an automatic solution for producing 3D geospatial information and new added-value services. This paper will first introduce AI4GEO initiative, context and overall objectives. It will then present the current status of the project and in particular it will focus on the innovative platform put in place to handle big 3D datasets for analytics needs and it will present the first results of 3D semantic segmentations and associated perspectives.