Local Binary Convolutional Neural Network for Facial Emotional Expressions Recognition

People

Alexandra Raibolt ( Lattes | E-mail )

Alberto Angonese ( Lattes | E-mail )

Gilson Giraldi ( Lattes | E-mail )

Paulo Rosa ( Lattes | E-mail )

Overview

This Jupyter Notebook shows step by step, the process of building a Local Binary Convolutional Neural Network for Emotional Expression Recognition in Python using the TensorFlow framework.

In this example we use the JAFFE dataset.

Notice: The LBCNN model proposed in this work was implemented in Python (version 2.7.12) using the TensorFlow framework (version 1.4.0) using a GPU based architecture, and might not work with other versions.

Dependencies

datetime
scipy.stats
sklearn.externals
sklearn.metrics
gzip
itertools
matplotlib
numpy
os
tensorflow
time

You can install missing dependencies with pip. And install TensorFlow via TensorFlow link.

Usage

Install the dependencies;
Run Jupyter Notebook in terminal to see the code in your browser.

Credits

Juefei-Xu, Felix, Vishnu Naresh Boddeti, and Marios Savvides. "Local binary convolutional neural networks." Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on. Vol. 1. 2017.
Lyons, Michael, et al. "Coding facial expressions with gabor wavelets." Automatic Face and Gesture Recognition, 1998. Proceedings. Third IEEE International Conference on. IEEE, 1998.
Hvass-Labs

License

Code released under the MIT license.