# Accurate Extraction of Cableways Based on the LS-PCA Combination Analysis Method
## 3 Experiment and Results
### Experimental Results and Analysis  
The three point cloud samples taken from the National Alpine Sking Center of the Beijing Winter Olympics were extracted sequentially using the method proposed in this paper. Following the processing of the first set of sample data, the results are shown in Figure 4a-d. \begin{table}
\begin{tabular}{c c c} \hline
**Category** & \multicolumn{2}{c}{**Configuration**} \\ \hline \multirow{3}{*}{Software} & Operating System & Win 11 \\  & Point-cloud Processing Library & PCL 1.11.1 \\  & Support Platform & Visual Studio 2019 \\ \hline \multirow{3}{*}{Hardware} & CPU & Intel(R)Core(TM)i5-9400F \\  & Memory & DDR4 32 GB \\ \cline{1-1}  & Graphics Card & Nvidia GTX 1080 Ti 11 GB \\ \hline \end{tabular}
\end{table} 
Table 1: Models and configuration parameters of software and hardware used in the test experiment. \begin{table}
\begin{tabular}{c c c c} \hline
**Data Name** & **Sample Number** & **Number of Ropeways** & **Number of Points** \\ \hline Group One & 1 & 4 & 1,018,921 \\ Group Two & 2 & 4 & 485,735 \\ Group Three & 3 & 4 & 557,785 \\ \hline \end{tabular}
\end{table} 
Table 2: The basic situation of each group of test sample data. Additionally, a gradient color is assigned to each sample point cloud based on its elevation. In Figure 4a, the front and side views of the first group of samples are shown before cableway segmentation and extraction. There is no doubt that the vegetation in the first group of samples is dense and some trees are tall, which presents great challenges in the extraction process. An illustration of the first set of samples after preliminary extraction is shown in Figure 4b. As shown in the figure, the point cloud obtained after preprocessing does not only include cables but also towers and vegetation point clouds that need to be further segmented and extracted. Based on the first set of samples, Figure 4c shows the front and side of the cableway segmented and extracted. From the figure, it is clear that whether viewed from the front or the side, the cableway point cloud has been well segmented and extracted. By fusing the two point clouds with different colors, the extracted ropeway and non-ropeway parts can be visually distinguished. In Figure 4d, the merged ropeway (white point) and non-ropeway (colored point) point clouds are represented as front and side views. As can be seen from the results of the first group of sample tests, the method proposed in this paper is effective in separating ropeway and non-ropeway components. The second set of samples is then tested separately. When the proposed cableway point cloud segmentation and extraction algorithm is applied to the second group of samples, the following processing results are obtained as shown in Figure 5a-d.  
As shown in Figure 5a, the second set of sample data is shown from both the front and side. The cableway will be difficult to extract due to some sporadic vegetation and trees in the picture. In Figure 5b, the front and side views of the second set of sample data after preprocessing are shown. The preprocessed data results are clearly superior, except for the cableway point cloud, which has only a few towers and vegetation point clouds. From the final segmentation and extraction of the second set of sample data, Figure 5c illustrates the front and side views of the cableway point cloud. The processing effect of this group of samples appears to be excellent. In Figure 5d, the ropeway point cloud (white) is compared with the non-ropeway point cloud (color). As can be seen intuitively, the method proposed in this paper still maintains good results in terms of segmenting and extracting cableway point clouds for the second set of test samples. Figure 4: There are the front and side views of the first set of sample point clouds (order from left to right): (**a**) before segmentation and extraction; (**b**) after preprocessing; (**c**) after completion of segmentation and extraction; and (**d**) the comparison display (marked as white and color).