pyaam - active appearance model

active appearance models implemented in python

Code based on https://github.com/marcovzla/pyaam

Instructions

Download MUCT dataset:

python -m pyaam.muct

View MUCT dataset:

./view_data.py

Train models:

./train_model.py shape
./train_model.py patches
./train_model.py detector
./train_model.py texture
./train_model.py combined

View models:

./view_model.py shape
./view_model.py patches
./view_model.py texture
./view_model.py combined

View face detector on webcam:

./view_face.py detector

View face tracker (patches):

./view_face.py tracker

Face tracker using AAMs coming soon!

References

• J. Saragih, "Non-rigid Face Tracking". In Mastering OpenCV with Practical Computer Vision Projects. PACKT, Oct 2012.
• M.B. Stegmann, "Active appearance models: Theory, extensions and cases". Master Thesis. 2nd edition. Informatics and Mathematical Modelling, Technical University of Denmark. Aug 2000.
• P. Martins, "Active Appearance Models for Facial Expression Recognition and Monocular Head Pose Estimation". MSc Thesis. Department of Electrical and Computer Engineering, University of Coimbra. June 2008.