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Scalismo Lab: Iterative Closest Points for rigid alignment

In this hands-on step, we will have our first encounter with the Iterative Closest Point (ICP) algorithm.

To keep things simple, we start here by applying this algorithm in the context of rigid alignment of meshes.

The goal is to align two meshes automatically, without the need of manually selecting landmarks, as we did before.

In the full track version, we will also check up on this method’s sensitivity to local minima.

To access the tutorial document:

  1. Switch to Scalismo Lab.
  2. Select the Iterative Closest Points for Rigid Alignment document under:
    Documents -> Fast track, for the fast track version
    Documents -> Full track, for the full track version

If you have questions, ask them in the comments section here on FutureLearn.

If you are doing the full track version, please remember that the exercises are optional. If you find them too hard, you can continue going through the tutorial without solving the exercises.

Did anything go wrong and you have a weird shape output? Post it in our Shapes Gone Wrong Padlet!

This article is from the free online course:

Statistical Shape Modelling: Computing the Human Anatomy

University of Basel