Semantic Morphable Model Tutorial

In this tutorial, you will learn all the components of semantic Morphable Models. The basic idea is to add semantics on a pixel level to our probabilistic Morphable Models: we have different models explaining different objects or parts of objects in the image - for each pixel we decide which model to choose. Occlusions are one of the core motivations behind the idea to explicitly segment the different components of the image - the tutorial is driven by this application and we will showcase you occlusion-aware Morphable Model adaptation.

Course Material:

During the tutorial you will use a segmentation algorithm, a robust illumination estimation technique and implement occlusion-aware Morphable Model adaptation.

This tutorial is an interactive software tutorial on the ideas of the following publication:

• Occlusion-aware 3D Morphable Models and an Illumination Prior for Face Image Analysis, Bernhard Egger, Sandro Schoenborn, Andreas Schneider, Adam Kortylewski, Andreas Morel-Forster, Clemens Blumer and Thomas Vetter, International Journal of Computer Vision, 2018

All course material is wrapped into single tutorial file that must be downloaded as a whole:
Download Semantic Morphable Model Tutorial

Requirements

• Modern CPU (two cores to keep the GUI responsive)
• Screen size > 800x600
• RAM 2GB
• Recent Java JVM, > 1.8.0_80 (Oracle and OpenJDK should work) (use 64 bit version if available)
• Download the Basel Face Model 2017 and add it to the data directory (model2017-1_face12_nomouth.h5).
• Make sure you start the tutorial in the working directory where the data folder is contained.

Memory Issues

To prevent memory issues, you can launch the tutorial using the extra JVM flag -Xmx with an explicitly set amount of memory. Use 2g for optimal results.

Start the tutorial with the command:

java -Xmx2g -jar SemanticMorphableModelTutorial.jar