# Wall Structure Geometry Verification Using TLS Data and BIM Model
## 1 Introduction
The mentioned applies to TLS in general, the advantage or disadvantage of the chosen method depends on the specific scenario, instrument, and application. The process of reconstruction of as-built BIM models from TLS data (scanned point clouds) is the so-called scan-to-BIM process [21; 22; 23]. As an analogy to this process, the comparison of the designed BIM model with the built structure from the TLS data is the scan-versus-BIM process. Several research efforts have been made in this area, which indicates the potential value of this process for progress monitoring and quality check of structural works. The scan-versus-BIM process is mostly divided into certain stages. To be able to compare the two models, in most cases this process starts with a transformation of the TLS data and the BIM model into the same coordinate system. This task can be executed in multiple ways, based on several survey points, or overlaps of surfaces (e.g., planar, spherical surfaces, etc.) between the two models. In addition, various techniques have been proposed for automated or semi-automated registration [24]. The second part of this process is deviation estimation, this part can also be done in various ways. Most frequently, it is realized by computing the minimum distances between the TLS data and the nearest surface from the BIM model for every point of the point cloud. Another frequently used way is to compute the distances in user-specified directions (e.g., in the direction of the common coordinate system axis, or the direction of the plane's normal vector, etc.). Further, in some applications, the point cloud is divided into segments based on the BIM model objects, i.e., each point of the point cloud is paired with the closest 3D object from the designed BIM with some tolerance (the segments are created as subsets in the close surroundings of the given structure). Then, each geometrical surface from the BIM model is compared with the paired sub-sets of points (identified and generated in the previous step). [PERSON] et al. in [25] converted the BIM model into a mesh model, from which point clouds were generated for each face of the building structure. The TLS point clouds were then downsampled to have the same density as the point clouds generated from the BIM model. Deviations were calculated as point-to-point distances between the closestpoints of the two point clouds. Segments with the highest deviations were highlighted to mark the areas that require additional inspections. The existing approaches compare the BIM model with the scanned cloud without detailed segmentation. The corresponding point cloud of the inspected element often contains objects that are not directly related to the surface of the element, which may affect the result when relative verification, e.g., when inspection of the flatness is performed. Another limitation is that they only check the difference in position of the chosen structural part and do not deal with the inspection of the geometric parameters. The contribution of the paper is a proposal of a new approach for verification of the position and also flatness of wall structures. The last part of the scan-versus-BIM process is the visualization of the computed deviations. There are also multiple possibilities, how to perform this task. The two most commonly used methodologies are color maps and contour lines. Individual setting of parameters for color maps can help to increase the lucidity of the results. Color maps can be divided into signed and unsigned. Unsigned color maps mean that the deviation values are visualized by their absolute value, so the points with the same absolute value will have the same color. On the other hand, in the case of signed color maps, the color for each value is visualized equivalently for positive and negative values. It is also possible to configure the range and the scale of the color map. Furthermore, for further processing and a better understanding of the results, a statistical analysis technique can be used to analyze the deviation patterns.