Local Binary Convolutional Neural Network for Facial Expression Recognition of Basic Emotions

People

Alexandra Raibolt ( Lattes | E-mail )

Alberto Angonese ( 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.

• The directory where the datasets should stay is not available in GitHub, since it would violate the dataset rules.

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

1. Install the dependencies;
2. 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.