Summer School on Probabilistic Morphable Models

A follow-up on the online course on statistical shape modelling

June 25th - June 29th, 2018
Basel, Switzerland

Endorsed by

Course overview

Probabilistic Morphable Models

Probabilistic Morphable Models are a fully probabilistic approach to model-based image analysis, based on:

  • the theory of Gaussian processes for modelling shapes
  • Markov chain Monte Carlo (MCMC) methods for model fitting
  • a software framework for efficient development of image analysis solutions.

This course teaches the theoretical basis of shape modelling and model fitting and provides an introduction on how to use the software framework Scalismo. The participants have the chance to apply the learned concepts and methods in a guided real-world project from the area of computer vision or medical image analysis.

Course organization

The course consists of two parts: An open online course and a summer school.

In the online course, participants learn the basic theory of shape modelling and are given a practical introduction to Scalismo. Participants of this course, who submit a solution to the course project, are invited to attend the summer school.

The summer school will focus on model-based image analysis. In theory lectures, participants will learn more about model-fitting and registration, with particular emphasis on probabilistic model-fitting using Markov Chain Monte Carlo methods. An important part of the summer-school is a project. Depending on their preference and background, the course participants can choose to work on a real-world problem from the field of medical image analysis or face image analysis.

Target audience

The intended audience for the course is beginning graduate students and researchers in computer vision and medical image analysis, who plan to apply statistical shape models as part of their work.

Prerequisite is good knowledge of basic probability theory and statistics as well as linear algebra. Participants should have basic programming skills in at least one programming language (ideally Java, C++ or Python).


Department of Mathematics and Computer Science Location of the Apaliving Basel Budget Hotel


Classes will take place at the Department of Mathematics and Computer Science of the University of Basel.


Basel is the third largest town in Switzerland. It can be reached by plane, by either flying directly to Basel Airport or to Zurich Airport (1-hour train ride to Basel).

Registration fee

The summer school is free of charge, but all participants need to organize their stay (travel, accommodation, food) by themselves.


Our main recommendation is the Apaliving Basel Budget Hotel. The price per night for a single room is approximately Fr. 90.--. In the same neighborhood, you can also find the following slightly cheaper options:

All these hotels are within walking distance of each other and located a 15 minute bus ride from the Department of Mathematics and Computer Science.

Instructors & Tutors

Thomas Vetter
Thomas Vetter is the founder and head of the Graphics and Vision Research Group of the University of Basel. Thomas Vetter’s research at the University of Basel is directed at automated synthesis and analysis of images.
Thomas Vetter
Marcel Lüthi
Marcel Lüthi is a lecturer at the University of Basel. His research focuses on the use of Gaussian Processes for shape modelling for application in medical image analysis.
Marcel Lüthi
Ghazi Bouabene
Ghazi Bouabene is a senior resarcher at the Graphics and Vision Resarch Group. He is one of the main developers of Scalismo, and has been working in several projects that aim at bringing shape modelling into industrial applications.
Ghazi Bouabene
Andreas Morél-Forster
Andreas Morél-Forster is a Postdoctoral Researcher at the Graphics and Vision research group. His research focuses on shape model fitting, using MCMC methods, with applications in both face image analysis and medical image analysis.
Andreas Morél-Forster


Online course (Feb 2018 - May 2018)

From To Subject
Mon 2/26     Sun 3/4     Basic concepts of shape modelling and the scalismo software.
Mon 3/5 Sun 3/11 Building shape models: fundamental concepts in theory and practice.
Mon 3/12 Sun 3/18 Probabilistic aspects of shape models.
Mon 3/19 Sun 3/25 Modelling with Gaussian Processes
Mon 3/26 Sun 4/1 Reconstructing missing parts
Mon 4/2 Sun 4/8 Fitting models to data
Mon 4/9 Sun 4/16 Model-based image analysis
Mon 4/16 Sun 4/25 Course Project

Summer school (June 25 - 29, 2018)

Day Time Subject
Mon 6/25 Morning Theory: The Analysis by Synthesis framework. (slides)
Theory: Non-rigid registration (slides)
Exercise: Non-rigid registration
Mon 6/25 Afternoon Plenum: Spotlight presentations by the participants
Setting up the IDE and the course projects.
Tue 6/26 Morning Theory: Bayesian Inference and probabilistic model fitting (part 1) (slides)
Exercise: Markov Chain Monte Carlo in Scalismo
Tue 6/26 Afternoon Project: Working on the course project
Wed 6/27 Morning Theory: Analysis of 2D face images using MCMC (slides)
Wed 6/27 Afternoon Project: Working on the course project
Thu 6/28 Morning Theory: Face image analysis - loocking back (slides)
Theory: Understanding the Metropolis-Hastings Algorithm (slides)
Thu 6/28 Afternoon Project: Working on the course project
Fri 6/29 Morning Theory: Advanced Topics in Gaussian processes and model-based image analysis (slides)
Scala - essential concepts (slides)
Fri 6/29 Afternoon Social Event
All classes start at 09.00 and will take place in lecture hall 00.003.


To register for the summer school, fill in the registration form below. Deadline for the registration is April, 30. 2018. Notification of acceptance will be given beginning of May.

Please note: A prerequisite for acceptance is the submission of the course project, which is part of the online course . Please submit your solution via email no later than April, 30. 2018.

For additional questions please send us an email to the address given below.