# Fast Cylinder Shape Matching Using Random Sample Consensus in Large Scale Point Cloud
## 6 Conclusions  
The method proposed in this paper shows that it is possible to estimate cylinder shape quickly in a point cloud. Sphere fitting was shown to be suitable for estimating the center axis of the cylinder, and the data were sampled for quick processing. The orientation of the constructed center axis data could be confirmed by PCA.  
PCA can be assumed to be the tangent of the estimation curve, since the main directionality can be set from the dispersion of the point data. The intersection of these estimated tangent lines can be a control point of the Catmull-Rom spline, and the curve can be obtained through it. The more accurate the center line estimate through the sphere fitting is, the better the curve can be. However, PCA can be more robust against noise and is relatively fast and accurate compared to spline fitting. The distinction between a straight line and a curve can be easily distinguished by using Equation (6).  
The proposed method has the advantage of estimating the linear/curved shape of the cylinder 10 times faster (22 times in Figure 13 and 17 times in Figure 14) than the comparison method while maintaining relative accuracy. In addition, more cylinders (less than 8 inches) were estimated. For center axis estimation, sphere fitting was performed with 1 cm error and using 25% data.  
Of course, it can be quickly matched to the constraints through vertical/horizontal conditions, but there is a disadvantage in that the oblique pipe cannot be estimated. In addition, the estimation of the curve in the comparison method matches the intersection of two straight lines only in a defined form with a number of cases. On the other hand, since the proposed method estimates along the actual bent path, it can be processed according to angles of all bent shape. Of course, there is a clue that point data should be smoother.  
The proposed method has its own merits, but there are disadvantages as well. When the density of point data is too high, it is necessary to search for more neighbors in order to process the curvature as a fit, which means the execution time is longer. Therefore, downsampling is required prior to cylinder fitting. Downsampling does not appear to be a major drawback, because it has a much lower opportunity cost than normal estimation or segmentation.  
Reverse engineering of construction modeling requires a lot of manual work. The more data there is, the harder it is for the operator to recognize the shape of the object. In other words, the more objects to recognize, the narrower the distance between objects, and the more difficult it is to distinguish objects on 2D screens. Therefore, fast recognition of primitive shapes is a good way to increase work efficiency. If it is forced to be accompanied by manual labor, it may be an effective alternative to obtain relatively quick estimation results rather than perfect automation. This paper is expected to improve the working efficiency of linear and curved cylinder estimation after center axis estimation without constraints and segmentation. Further study will be conducted in a way that smoothly integrates the estimated straight lines and curved parts into one and can produce consistent results.  
Conceptualization, Y.-H.J.; Methodology, Y.-H.J.; Software, Y.-H.J.; Supervision, W.-H.L.; Visualization, Y.-H.J.; Writing--original draft, Y.-H.J.; Writing--review & editing, Y.-H.J.  
The authors declare no conflict of interest.