# Influence of Material on the Density of a Point Cloud Created Using a Structured-Light 3D Scanner
## 3 Materials and Methods
### Methodology  
The research was focused on investigating the relationship between the material, its surface characteristics, and the density of the scanned point clouds. Point cloud density was used as the main indicator, but while performing the experiments, some other issues were raised. These issues are horizontal lines in the point cloud, missing points in the middle of the scanned area, and the excessive point noise of the point cloud. More details on these issues are provided in the Results section. It was necessary to select the materials on which experiments were made. Previously described selection processes and methods (e.g., [27]) often stress a specification of selection criteria. The materials used for the experiments were selected on the basis of the following three criteria:  
* The materials are commonly used on the surface of buildings. * There is a sufficient diversity of the materials. * The materials have not yet been investigated regarding their influence on point cloud density. For some materials, the influence of various treatments on point cloud density has also been tested. These treatments could at least partially eliminate a material's undesirable properties and improve the resulting point cloud density and, consequently, the polygon network generated from the point cloud. The treatments are briefly described in the Methodology of Scanning Results Evaluation subsection. More details about surface treatments' application to the particular materials, together with the influence of the treatments on point cloud density, are given in the Results section. From the existing objective metrics of the point cloud density assessment [17], we chose point-to-point quality metrics, which are commonly used [17; 28]. This method compares the degraded point cloud and the original point cloud point by point, even if both clouds do not have the same number of points. Furthermore, a multi-scale model for cloud comparison modeling (M3C2) was used, as the method allows the combination of data from multiple scan positions or data sources with different degrees of uncertainty [29]. The distance between points and finding the nearest neighbor in a point cloud measure point-to-point quality metrics. For each point in the reference point cloud \(A\), the nearest neighbor that is in the degraded point cloud \(B\) is found [17]. The resulting distance between two points is called the error vector dB, \({}^{A}(i)\) and can be evaluated in two ways point-to-point, as follows. The Hausdorff (Haus) metric is the maximum distance that can be measured between all points in cloud \(B\) and their nearest neighbor in reference cloud \(A\). The Hausdorff distance is defined as follows [17]:  
\[d_{Haus}=\max_{\forall i\in B}d^{B,A}(i) \tag{3}\]  
By averaging the distance from all points in \(B\) (the number of NB points) and their nearest neighboring points in reference cloud \(A\), the average distance, or root mean square distance (RMSD), is produced, as follows [17]:  
\[d_{RMSD}=\frac{1}{N_{B}}\sum_{i=1}^{N_{B}}d^{B,A}(i) \tag{4}\]  
The above metrics (both RMSD and Hausdorff) are calculated symmetrically in both directions. The distance is calculated between \(B\) and \(A\) (dB, \(A\)) and between \(A\) and \(B\) (dA, \(B\)). The maximum operator is used to obtain the symmetric versions of the ds RMSD and Hausdorff metrics, as follows: [17]:  
\[d^{S}_{RMSD}=\max\Bigl{(}d^{A,B}_{RMSD},d^{B,A}_{RMSD}\Bigr{)} \tag{5}\]  
\[d^{S}_{Haus}=\max\Bigl{(}d^{A,B}_{Haus},d^{B,A}_{Haus}\Bigr{)} \tag{6}\]  
The following materials were selected and scanned: \begin{tabular}{l l}
1. Hairy substance; & 7. Wooden parquets; \\
2. Transparent holographic foil; & 8. Reed; \\
3. Clear textured glass; & 9. Granite; \\
4. Woven carpet; & 10. Marlstone; \\
5. Glazed roof tile; & 11. Sheet metal; \\
6. Full burnt brick; & 12. Polycarbonate. \\ \end{tabular}   
All samples of materials were taken during the reconstruction of existing buildings. These are old or historical materials from buildings located in the Czech Republic.