Probabilistic Morphable Models
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Online course and Summer school

Online Course
Feb. 18th - April 13th on FutureLearn

Summer school
June 3rd - June 8th, 2019, 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).

Information


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

Venue

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

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.

Accommodation

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

Programme


Online course (Feb 2018 - May 2018)

From To Subject
Mon 2/18     Sun 2/24     Basic concepts of shape modelling and the scalismo software.
Mon 2/25 Sun 3/4 Building shape models: fundamental concepts in theory and practice.
Mon 3/4 Sun 3/10 Probabilistic aspects of shape models.
Mon 3/11 Sun 3/17 Modelling with Gaussian Processes
Mon 3/18 Sun 3/24 Reconstructing missing parts
Mon 3/25 Sun 3/31 Fitting models to data
Mon 4/1 Sun 4/7 Model-based image analysis
Mon 4/8 Sun 4/14 Course Project

Tentative Program of the Summer school (June 3 - 8, 2019)

Day Time Subject
Mon 6/3 Morning Theory: The Analysis by Synthesis framework.
Theory: Non-rigid registration
Mon 6/3 Afternoon Plenum: Spotlight presentations by the participants
Setting up the course projects
Tue 6/4 Morning Theory: Bayesian Inference and probabilistic model fitting (part 1)
Exercise: Markov Chain Monte Carlo in Scalismo
Tue 6/4 Afternoon Project: Working on the course project
Wed 6/5 Morning Theory: Analysis of 2D face images using MCMC
Wed 6/5 Afternoon Project: Working on the course project
Thu 6/6 Morning Theory: Face image analysis - a look back
Theory: Understanding the Metropolis-Hastings Algorithm
Thu 6/6 Afternoon Project: Working on the course project
Fri 6/7 Morning Theory: Advanced Topics in Gaussian processes and model-based image analysis
Presentations of the course project
Fri 6/7 Afternoon Social Event

Registration


To registration for the online course, please go directly to FutureLearn.

To register for the summer school, please send an e-mail to the address below. Note that the summer school is free of charge, but requires some investment of time from your side. A prerequisite for admission is the successfully completion the course project, which is part of the online course.