A 3D point cloud is a most complete 3D representation containing points with associated coordinates, color and other properties. Point cloud processing and semantic understanding are very active research topics

Room segmentation allows to automatically partition huge point cloud data containing millions of points into semantically meaningful parts, like buildings and rooms. To solve this problem, one typically uses machine learning.

Object segmentation and matching allows to automatically recognize the objects within indoor environments. To solve this challenging problem, deep learning is commonly used. The recognized objects can be further used for applications, such as architecture, robot navigation and improved building management.