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:
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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.
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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
- Install the dependencies;
- Run Jupyter Notebook in terminal to see the code in your browser.
Credits
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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.
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Lyons, Michael, et al. "Coding facial expressions with gabor wavelets." Automatic Face and Gesture Recognition, 1998. Proceedings. Third IEEE International Conference on. IEEE, 1998.
License
Code released under the MIT license.