Week 1: Analysis by synthesis

Where we discuss the analysis by synthesis paradigm to shape and image analysis and given an introduction to Bayesian inference.

Week 2: Basics of Markov Chain Monte Carlo

Where we introduce the Metropolis Hastings algorithm, and use it in Scalismo to do Bayesian regression on our hand dataset.

Week 3: Shape model fitting with MCMC

Where we show how MCMC enable us to obtain fully probabilistic solutions to shape model fitting problems.

Week 4: Designing effective proposals

Where we discuss how to speed up our samples using targeted proposal distributions.