Semantic Labeling of Indoor Environments from 3D RGB Maps
Manuel Brucker, Maximilian Durner, Rareş Ambruş, Zoltán-Csaba Márton, Axel Wendt, Patric Jensfelt, Kai O. Arras, Rudolph Triebel · 2018
We present an approach to automatically assign semantic labels to rooms reconstructed from 3D RGB maps of apartments. Evidence for the room types is generated using state-of-the-art deep-learning techniques for scene classification and object detection based on automatically generated virtual RGB views, as well as from a geometric analysis of the map's 3D structure. The evidence is merged in a conditional random field, using statistics mined from different datasets of indoor environments. We evaluate our approach qualitatively and quantitatively and compare it to related methods.