Line Structure-Based Indoor and Outdoor Integration Using Backpacked and TLS Point Cloud Data

Chenglu Wen, Xiaotian Sun, Shiwei Hou, Jinbin Tan, Yudi Dai, Cheng Wang, Jonathan Li

Abstract: This letter presents a line structure-based method for integration of centimeter-level indoor backpacked scanning point clouds and millimeter-level outdoor terrestrial laser scanning point clouds. Using 3-D lines for registration, instead of matching points directly, can improve the robustness of the method and adapt to multisource point cloud data of different qualities. Considering the limited overlapping between indoor and outdoor scenes, line structures are extracted from overlapped wall areas that may be included in interior and exterior data. Here, a patch-based method labels a point cloud into wall, ceiling, floor categories, as well as assigning the candidate overlapping walls. Then, lines structures are extracted from the wall plane point cloud. Potential door and window line structures are detected and refined for point cloud registration. Last, an iterative closest point-based method is used to fine tune the registration results. Our results show that the proposed method effectively integrates a promising map of indoor and outdoor scenes.