Paper 12269-15
Paper 12269-15
Reconstruction of 3D models of infrastructure objects from satellite images based on typed elements
On demand | Presented live 6 September 2022 
Abstract
The paper describes an approach to restoring a three-dimensional model of rigid objects from a single satellite image based on informative classes identified from the results of machine learning, which include railway rails and poles, roofs and walls of buildings, shadows of poles and buildings, and others. The proposed algorithms take into account various conditions for the presence of certain classes in the image, identified by the results of machine learning, as well as the conditions for the absence of metadata on the spatial resolution and spatial orientation of the shooting and the Sun (shooting angle, scanning azimuth, etc.).
Presenter
Moscow State Univ. of Technology "STANKIN" (Russian Federation)
Evgenii Semenishchev is the research of the Center for Cognitive Technology and Machine Vision at Moscow State University of Technology “STANKIN,” Moscow, Russian Federation. He received his BS (2005), MS (2007) in the communication system from the South-Russian State University of Economics and Service, and his Ph.D. in technics from Southern Federal University (2009). Evgeni is a member of SPIE society. His research interests include image processing, image fusion and computer vision.