## 3 Results and Discussion
### Sparse Point Cloud  
The analysis of the resulting sparse clouds is summarized in Table 8 and Figure 11. The third column represents the size of each sparse point cloud--that is, the number of tie points successfully reconstructed in the alignment process. As indicated earlier, the higher number of cloud points of the DC's clouds compared with the SP's is attributed mainly to the higher resolution of the digital camera. The fourth column represents the averaged point size in pixels of all the 3D points in the sparse cloud. The size of a given point is the sigma value (\(\sigma\)) of the Gaussian blur of the scale level in the Gaussian pyramid at which this particular point was detected within the SIFT algorithm. The point size is approximately the same in both cameras' data sets. The fifth column in the table provides information regarding the colors of the points in each cloud, which are represented in three bands (RGB). However, the depth of colors varies; with the digital camera, the depth is 16 bit, which gives a better representation of the real colors compared with the smartphone 8 bit. This difference is because of the image format with which the images were captured. For the digital camera, the images were taken in RAW format (.NEF), which prevents any auto adjustment or image compression. On the other hand, the JPG format compresses the smartphone images to minimize their size, resulting in losing color data. Figure 10: Bar charts represent the four targets reconstruction parameters. (**a**) The average percentage of projections contributed to reconstructing the four target points for both cameras in all data sets; (**b**) the average RMS reprojection error of the four targets for each data set for both cameras. DC, digital compact camera; SP, smartphone camera. To examine the difference in color representation, the histograms of the color bands (R, G, B) and their combination are generated for both cameras based on the beam sparse cloud, Figures 12 and 13. The horizontal axis represents the corresponding color range from 0 to 255, whereas the vertical axis represents the number of points in the sparse cloud having the same color range. The points in the DC's sparse cloud lies within a red channel range of 50-200 with a normal distribution mean value = 141, a green channel range of 30-210 with a normal distribution mean value = 135, and within a wider blue color range of 10-255 with a normal distribution mean value = 128. On the other hand, the color ranges of the smartphone's sparse points are noticeably shifted to the right on the horizontal axis. The points are within a red channel range of 70-220 with a normal distribution mean value = 162, a green channel range of 40-230 with a normal distribution mean value = 148, and a blue channel range of 30-255 with a normal distribution mean value of 140. As indicated, there is a considerable shift to the right in the color values for the SP's sparse cloud suggesting a higher intensity associated with its points compared with the DC's. This  
Figure 11: Sparse point clouds of the three specimens (square beam, cylinder, sandpile) reconstructed from: (**a–c**) the digital camera data; (**d–f**) the smartphone data. All clouds are scaled in meters, and the provided scale bar is in meters. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Specimen** & **Capturing Device** & **Cloud Size** & **Point** & **Point** & **Processing** & **Memory Usage** \\ \hline \multirow{3}{*}{Beam} & DC & 194,535 & 4.57 & 3B, U16 & 5.62 & 2.01 \\  & SP & 84,572 & 4.54 & 3B, U8 & 6.03 & 1.33 \\ \cline{1-1}  & DC & 91,634 & 4.86 & 3B, U16 & 3.83 & 1.67 \\ \cline{1-1}  & SP & 82,189 & 4.57 & 3B, U8 & 4.12 & 1.17 \\ \cline{1-1}  & DC & 115,289 & 4.18 & 3B, U16 & 6.58 & 1.72 \\ \cline{1-1}  & SP & 78,321 & 4.37 & 3B, U8 & 6.26 & 1.37 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: The sparse point clouds’ parameters of both cameras’ data sets.