This project addresses the current technological difficulties of rapid and automatic reconstruction of large-scale areas and seeks solutions for the development of accurate, robust and scalable methods and systems for processing the big data captured by active and passive sensors in order to produce a realistic virtual representation. More specifically the research program proposes further study and development of novel and robust algorithms for accurately detecting and extracting:
(a) structural information from data captured from passive and active remote sensors i.e. aerial/satellite images and LiDAR, and reconstructing the geometry of the terrain, buildings, cars and tree models representing the acquired area,
(b) appearance information from imagery captured from ground, oblique-aerial and satellite sensors, and fusing this information into realistic composite texture atlases of the 3D models.
This fundamental research is funded by: