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.
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
- Modern CPU (two cores to keep the GUI responsive)
- Screen size > 800x600
- RAM 2GB
- Recent Java 8 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.
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