How to superimpose unordered point clouds of arbitrary size using open3d

[usccolumbia]

as the author pointed out:
Note: This function does not attempt to determine which pairs of points from either cloud correspond. Instead, it infers them from the order of the arrays. (It assumes that the i'th point from X corresponds to the i'th point from x.)

This assumption does not hold for generic point cloud registration such as atom point clouds of crystals.
If you want to do superpose3d for un-ordered points, you'd better try open3d, which I have spent a lot of effort to make it work.

import open3d as o3d
import numpy as np
source = o3d.geometry.PointCloud()
target = o3d.geometry.PointCloud()

np.random.seed(0)
pointset = np.random.rand(10, 3)
source.points = o3d.utility.Vector3dVector(pointset) # Random points

Generate target point cloud

target.points = o3d.utility.Vector3dVector(pointset) # Random points
target.transform([[1, 0, 0, 0.5],
[0, 1, 0., 0.0],
[0, 0.2, 1, 0],
[0, 0, 0, 1]])

Apply ICP registration

threshold = 5
trans_init = np.identity(4) # Initial transformation matrix
reg_p2p = o3d.pipelines.registration.registration_icp(
source, target, threshold, trans_init,
o3d.pipelines.registration.TransformationEstimationPointToPoint(),
o3d.pipelines.registration.ICPConvergenceCriteria(max_iteration=1000))

print("Transformation matrix:")
print(reg_p2p.transformation)

print("Matching points:")
print(np.asarray(reg_p2p.correspondence_set))
print(f"% of match:{reg_p2p.fitness*100}%")
print(reg_p2p.inlier_rmse)

[jewettaij]

This is awesome, usccolumbia! I'll post a link to it on the front page.