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Scalismo Lab: Gaussian Process sampling and marginalisation

Practice Gaussian Process marginalisation in Scalismo Lab and obtain a statistical nose model out of a given face model.
© University of Basel
In this hands-on step, we will extend on the previous tutorial video and have a closer look at the difference between discrete and continuous Gaussian Processes and the concept of marginalisation.

We will start by first learning how to obtain continuous Gaussian Processes from discrete ones and understand what sampling from such a process provides.

We will then focus on going the other way round, that is from continuous to discrete, and apply the concept of marginalisation to both Gaussian Processes and statistical mesh models in Scalismo. Doing so, we will learn how to build a marginal nose model out of a given statistical face model.

In the full track version, we will also learn how to compare the probability of shapes, or noses in this case, according to a given shape model.

To access the tutorial document:

  1. Switch to Scalismo Lab.
  2. Select the Gaussian Processes Sampling and Marginalisation 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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