A knowledge-based approach to the automatic algorithm selection for 3D scene annotation

In this paper we present a novel approach for 3D point cloud processing with the aim of annotating objects in a scanned scene. Our method is based on human cognition to guide the 3D processing algorithms and uses semantic knowledge to manage data and identify immediate situation-dependent objectives. In particular, we have built a system that allows an automatic and flexible selection of algorithms. The selection strategy exploits knowledge to identify the geometrical features to be detected as well as the objects to be annotated at each stage of the 3D processing of the point cloud.