Automatic Point Cloud Modelling for BIM in AEC Sector

Sammanfattning

In this research, automatic point cloud modeling strategies have been tested to find the best strategies to model walls, floors and ceilings classes in terms of processing time and accuracy. The modeling was applied on a point cloud data related to the Architecture, Engineering, and Construction field which is a point cloud of a building collected by Sweco company in Sweden. This point cloud was segmented and classified into two classes: the first class is walls, and the second is floors and ceilings. The strategies were applied on each class using two commercial software which are: Leica Cyclone 3D-R and Pointfuse and one free open source software which is BLENDER. The strategies were formed by making a collection of parameters for each strategy, some of these parameters are numeric and others are non numeric. The strategies were three combinations: in the first combination the default values of the numerical parameters were used. In the second combination these default values were increased by 50% and in the third combination these default values were decreased by 50%. The final results showed that all best strategies were done by using Leica Cyclone 3D-R software. Regarding the processing time to model the walls, the fastest strategy is by increasing the default numerical parameters of Regular Sampling function by 50% while ignoring the scanning directions. Regarding the processing time to model the floors and ceilings. The fastest strategy is also by increasing the default numerical parameters of meshing in two steps function by 50% which in the first step of the function the try to create watertight mesh option is chosen for hole management method and the scanning directions are not ignored. In the second step the refine mesh without cloud option is chosen for refining method and under this option the following parameters are defined: deviation error, refine on free borders is not included and preserve sharp edges is included. Regarding the accuracy, the most accurate strategy to model the walls is by decreasing the default numerical parameters of meshing in two steps function by 50% which in the first step of the function the hole detection option is chosen for hole management method and the scanning directions are included. In the second step the refine mesh from cloud option is chosen for refining method and under this option the following parameters are defined: meshing by keep only best points, deviation error, distance, local reorganization is included and no free border modification is chosen for hole management method. Regarding the most accurate strategy to model the floors and ceilings is by decreasing the default numerical parameters of meshing in two steps function by 50% which in the first step of the function the hole detection option is chosen for hole management method and the scanning directions are included. In the second step the refine mesh from cloud interpolation option is chosen for refining method and under this option the following parameters are defined: refine with deviation error for refining method, deviation error, maximum number of triangles, minimum triangle size, refine with point evenly spaced is not included, distance is included, local reorganization is included, angle threshold on scanning directions is not include and refine free border is chosen for hole management method.