A multi-agent method for automatic building recognition based on the fusion of lidar range and intensity data

Lidar has proved to be a promising data source for various mapping and 3D modeling of buildings in urban areas. Therefore, many researchers have been trying to study and develop automatic building recognition algorithms based on Lidar data. But, according to the complicated relationships between buildings and other objects in urban areas, especially trees and vegetations, the performance of obtained results from most of these algorithms is still dependent to several assumptions and simplifications. In this paper a multi-agent methodology has been proposed for automatic building recognition based on the fusion of textural and spatial information extracted from Lidar range and intensity data. The evaluation of obtained results confirms the high capabilities of this proposed multi-agent algorithm to decrease the conflicts in the field of automatic building recognition in complex urban areas.