For using ICP on your dataset see the icp.py file. The usage is as follows: (R, t) = IterativeClosestPoint(source_pts, target_pts, tau) where R and t are the estimated rotation and translation using ...

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The iterative closest point (ICP) algorithm is widely used in three-dimensional (3D) point cloud registration, and it is very stable and robust. However, its biggest drawback is being easily trapped ...

The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of three-dimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been ...