未完
待讀參考：
https://blog.csdn.net/kaspar1992/article/details/54836222
https://www.cnblogs.com/yin52133/archive/2012/07/21/2602562.html
https://blog.csdn.net/u011600592/article/details/70258097
https://blog.csdn.net/Ha_ku/article/details/79755623
https://www.cnblogs.com/21207-iHome/p/6038853.html
https://www.cnblogs.com/sddai/p/6129437.html
論文：方法比較 [Rusinkiewicz et Levoy, 2001], [GRUEN et AKCA, 2005] et [AKCA, 2007]
課堂筆記：
RANSAC算法（RANdom SAmple Consensus隨機抽樣一致）
ICP算法（Iterative Closest Point迭代最近點）
目的: estimate transform between two dense sets of points
步驟：
1. Assign each point in {Set 1} to its nearest neighbor in {Set 2}
2. Estimate transformation parameters – e.g., least squares or robust least squares
3. Transform the points in {Set 1} using estimated parameters
4. Repeat steps 1-3 until change is very small
可行的預處理：去除離散的噪點。
擴展：PCL雲點集