Automatic creation of semantically rich 3D building models from laser scanner data

Abstract

Laser scanners are increasingly used to create semantically rich 3D models of buildings for civil engineering applications such as planning renovations, space usage planning, and building maintenance. Currently these models are created manually -a time-consuming and error-prone process. This paper presents a method to automatically convert the raw 3D point data from a laser scanner positioned at multiple locations throughout a building into a compact, semantically rich model. Our algorithm is capable of identifying and modeling the main structural components of an indoor environment (walls, floors, ceilings, windows, and doorways) despite the presence of significant clutter and occlusion, which occur frequently in natural indoor environments. Our method begins by extracting planar patches from a voxelized version of the input point cloud. We use a conditional random field model to learn contextual relationships between patches and use this knowledge to automatically label patches as walls, ceilings, or floors. Then, we perform a detailed analysis of the recognized surfaces to locate windows and doorways. This process uses visibility reasoning to fuse measurements from different scan locations and to identify occluded regions and holes in the surface. Next, we use a learning algorithm to intelligently estimate the shape of window and doorway openings even when partially occluded. Finally, occluded regions on the surfaces are filled in using a 3D inpainting algorithm. We evaluated the method on a large, highly cluttered data set of a building with forty separate rooms yielding promising results.

Challenges and Opportunities for Implementation of Laser Scanners in Building Construction

“…For example, several studies attempt to use laser scanners for as-built creation [27,36]. However, there are two main problems in this area.…”

“…First, geometric information such as lines and surfaces cannot be easily extracted from millions of points data of objects [1], and are recommended as future research [1,4]. Second, a limited number of scanners such as terrestrial scanners are suitable for BIM [36], and the state-of-the-art technologies have not been investigated fully.…”

Automatic Room Segmentation of 3D Laser Data Using Morphological Processing

“…total number of pixels matched total number of pixels detected automatically (2) Completeness = total number of pixels matched total number of pixels detected manually (3)…”

“…BIM can be used to evaluate design, reduce construction and maintenance costs, support building management, and enhance collaboration and information sharing. However, the majority of existing buildings lack BIM [2][3][4]. Even where existing buildings have BIM, often it does not represent the current situation, particularly in cases of continual remodeling or renovation [5].…”

Flexible Earthwork BIM Module Framework for Road Project

“…It is a faster and more efficient way of collecting data as explained by Slattery [2]. Different researchers have provided a remarkable effort regarding earthwork surface modeling and data collection technologies for 3D models [6,7]. Randall [8] explained laser scanning importance for BIM modeling, and Sepasgozar [9] described the challenges being faced in using these technologies.…”