3D Object Mapping Using a Labelling System

Abstract

3D data has arisen as the most used information for environment representation thanks to the advent of low cost RGB-D cameras. We propose a 3D map representation that uses not only depth information but the information provided by an expert system. This expert consists on a Convolutional Neural Network trained with deep learning techniques for scene labelling purposes. For every partial 3D map captured, we receive a set of labels with their associated probability of presence in that scene. The final map is obtained by registering and merging all these partial maps. The semantic labels from the expert system are used to recognise and locate objects in the environment.