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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.

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.

lbcnn's People

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