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Model fitting and correspondence

In this video, we will discuss how to analyse a given shape using the shape model. To this end, we introduce a simple algorithm called the Iterative Closest Point (ICP) …

A visit to surgeon Dr Metzger

After studying a lot of theory and working through a lot of Scalismo Lab exercises, we now invite you to have a look at the application of shape modelling technology …

Scalismo Lab: posterior shape models

In this hands-on step, we will focus on part of what we have seen in the previous tutorial video and learn how to perform Gaussian Process regression and build posterior …

Posterior models for different kernels

In this short article, we will visually compare the prior and posterior for different Gaussian Process models. Specifically, we will look at how the variance is changed by incorporating known …

Gaussian Process regression

In many practical applications of shape modelling the goal is to infer the full shape from given partial observations. Gaussian Process regression is an inference technique that can be used …

The regression problem

A common task in shape modelling is to infer the full shape from a set of measurements of the shape. This task can be formalised as a regression problem. In …

Femur project: first step

You are now ready to start working on your own shape modelling project: reconstructing partial femur shapes. Please note that this project is optional. You can continue your learning journey …

Congratulations and outlook

Congratulations to you all on your successful conclusion of our course’s first half! After a brief recapitulation of what you’ve learned so far, we will show you further applications of …

Wrapping up: Week 7

In this week we completed our toolchain with an algorithm for fitting a shape model to an image. We have seen the classic algorithm called Active Shape Model fitting. Active …