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Scalismo Lab: model fitting with Iterative Closest Points

Learn how to fit a shape model to a target mesh using the Iterative Closest Point (ICP) method in Scalismo Lab.
© University of Basel

In this hands-on step, we will reproduce the model fitting task seen in the previous tutorial video.

Now that we are familiar with the Iterative Closest Point (ICP) algorithm, we will use it in combination with Gaussian Process regression to find correspondences between a face model and a target face for a small set of characteristic points.

We will then extend this method such that a large number of points can be processed.

To access the tutorial document:

  1. Switch to Scalismo Lab.
  2. Select the Model Fitting with Iterative Closest Points 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!

© University of Basel
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Statistical Shape Modelling: Computing the Human Anatomy

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