LBCNN
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Local Binary Convolutional Neural Network for Facial Expression Recognition of Basic Emotions in Python using the TensorFlow framework
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.