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Model Training

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Tadas Baltrusaitis edited this page May 11, 2018 · 3 revisions

There are a number of trained models that OpenFace uses and the code used for training them is available.

Facial Landmark Detection

OpenFace uses the Convolutional Expert Constrained Local Model model for facial landmark detection, it requires three trained modules - Point Distribution Model, Patch Experts, and landmark verification module.

Point Distribution model

To train the statistical model of shape go to: model_training/pdm_generation and read the readme file there

More details here in Chapter 4.2 specifically 4.2.5

Patch Experts

You can find the patch expert training code here:

  • ./model_training/ce-clm_training for CEN patch expert training
  • ./model_training/ccnf for LNF and SVR patch expert training

Face validation

A module for validating face detections (training and inference), it is used for tracking in videos so as to know when reinitialisation is needed: matlab_version/face_validation

Follow the readme there for instructions

Action Unit recognition

More information about Facial Action Units can be found here - https://github.com/TadasBaltrusaitis/OpenFace/wiki/Action-Units

To train Facial Action Unit detectors follow the instructions in the readme file: model_training/AU_training

More details about the method used here

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