- #1

preet

- 98

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I have two sets of point cloud data (points in xyz) representing the same geometric shape. However, the point cloud data does not correspond -- both clouds have a different number of points and there is no relation between the two clouds other than the fact that they represent a similar geometric shape.

The goal is to register one of these point clouds to the other one using only rigid transformation (translation, rotation).

I'm not sure how to approach this problem -- a lot of the information I've found on the internet points the Iterative Closest Point algorithm, which involves defining a function to measure the disparity between the two point sets and then minimizing it to converge to a solution. However, I don't know how to define a function to measure the disparity between the two point sets I've described, since the points do not correspond.

tldr;

How do I define a 'distance' or 'disparity' function between two sets of point clouds that do not correspond but represent a similar geometric structure?

TiA,

-preet