  In this paper we propose an approach to perform semantic segmentation of 3D
point cloud data by importing the geographic information from a 2D GIS layer
(OpenStreetMap). The proposed automatic procedure identifies meaningful units
such as buildings and adjusts their locations to achieve best fit between the
GIS polygonal perimeters and the point cloud. Our processing pipeline is
presented and illustrated by segmenting point cloud data of Trinity College
Dublin (Ireland) campus constructed from optical imagery collected by a drone.
