## 2 Related Work  
Because they are fast, simple to use, and highly accurate, mobile 3D scanners are widely used for existing-structure data acquisition for 3D indoor scenes. However, semantically rich 3D indoor model creation of building interiors using scanned point clouds encounters critical difficulties: the complex design of indoor structures, not to mention obstacles, requires time-consuming manual operation and thus large data sizes, which often leads to system slowdown or even complete failure. In current practice, the creation of accurate 3D indoor models is largely an interactive process performed by service providers who are contracted to scan and model a facility [20]. A project might require several months to complete, depending on the complexity of the facility and modeling requirements [4]. The basic geometric modeling process for manual creation of a 3D indoor model involves fitting geometric primitives to the 3D point cloud directly. Existing commercial software typically includes tools for fitting geometric primitives such as planes, cylinders, spheres, and cones to the point cloud [21; 22]. These tools are semi-automated and require significant user input. For example, to model a planar surface, the user selects a few points or a patch of data, and a plane is fitted to the selected data [23]. In this way, approximate boundaries of the patch can be identified, but in practice, these boundaries can be irregular and inaccurate. To improve the efficiency and accuracy of the modeling process, some researchers have proposed semi-automatic modeling methods through using cross-sections and surface extrusion algorithms. A semi-automatic methodology for improved productivity in as-built BIM creation with respect to large and complex indoor environments is proposed in [24]. In this approach, the plane feature and remaining points are automatically extracted from the point cloud and used as a reference to facilitate the manual construction of the as-build BIM. [15] present similar work. Their method generates the BIM model by importing a 3D wireframe model into BIM tools for manual as-build modeling. Because the same types of primitives must be modeled throughout a facility, the steps are highly repetitive and tedious [25; 26]. In addition, due to the complexity and uniqueness of specific buildings, modelers must be highly skilled and proficient. Even with training, decisions about exactly what elements to model and how to model them are sufficiently subjective to cause significant variability in the quality of the models produced by different personnel. To manage this problem, some recent studies have looked to full automation. [PERSON] et al. presented an automated method to create accurate 2D floor plane models of building interiors from a 3D point cloud [27]. This method involves creating a histogram of height data to detect floor and ceiling data, and then extracting the line segments corresponding to walls based on the point density of the projected remaining points. [PERSON] and [PERSON] developed a volume sweep and cell decomposition method for the reconstruction of Manhattan-world interior scenes from point clouds [28]. The output is a 3D CAD model of indoor environments, but the key assumption is the absence of furniture or small objects. Moreover, this method is only applied in a single room or space and the openings are not taken into consideration. In the approach proposed by [PERSON] and [PERSON], points are classified into floor, ceiling, wall, and remaining points using point normal orientations [29]. The planar patches of floors, ceilings, and walls are fitted and the boundaries are estimated using alpha shapes. [PERSON] and [PERSON] propose a 3D reconstruction method for interior wall surfaces under high levels of occlusion and missing data [30]. They recover occlude parts of reconstruction surfaces and perform opening detection using a Support Vector Machine (SVM) algorithm. Using knowledge of different types of elements and the contextual relationships between them, [PERSON] et al.