Towards a realistic indoor world reconstruction: preliminary results for an object-oriented 3D RGB-D mapping

A real world reconstruction that generates cyberspace not from a computer graphics tool, but from the real world, has been one of the main issues in two different communities of robotics and computer vision under different names of Simultaneous Localization And Mapping (SLAM) and Structure from Motion (SfM). However, there have been few trials that actively integrate SLAM and SfM for possible synergy. This paper shows the real world reconstruction can be enabled through this integration. As a result, the preliminary map has been generated of which five subgoals are: Realistic view (RGB), accurate geometry (depth), applicability to multi-floor indoor building, initial classification of a possible set of objects, and full automation. To this end, an engineering framework of “Acquire-Build-Comprehend (ABC)” is proposed, through which a sensor system acquires an RGB-Depth point cloud from the real world, builds a three-dimensional map, and comprehends this map to yield the possible set of objects. Its performance is demonstrated by building a map for three levels of indoor building of which volume is 1,408 m³.