mahakal / facialemotionrecognition

Using Extended Cohn-Kanade AU-Coded Facial Expression Database to classify basic human facial emotion expressions using ann

Facial-Emotion-Recoginiton

Overview

Using Extended Cohn-Kanade AU-Coded Facial Expression Database to classify basic human facial emotion expressions using ann.

Installation

The necessary dependencies are in the requirements.txt file so just run this before running the actual code to get them installed. May require some extra effort for OpenCV though.

pip3 install -r requirements.txt

Usage

If you want a facial emotion classifier you can just download the Cohn-Kanade dataset and serialize the dataset according to your need and if you can you should also use another dataset with ck for better results.

pickle_dataset.py => Script for processing and Serializing dataset. python pickle_dataset.py -h

cnn.py => Convolution Neural Network to train the the classifier. python cnn.py -h

cohn-kanade-images.txt => Contains some basic info about the dataset.

Credits

• Kanade, T., Cohn, J. F., & Tian, Y. (2000). Comprehensive database for facial expression analysis. Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition (FG'00), Grenoble, France, 46-53.
• Lucey, P., Cohn, J. F., Kanade, T., Saragih, J., Ambadar, Z., & Matthews, I. (2010). The Extended Cohn-Kanade Dataset (CK+): A complete expression dataset for action unit and emotion-specified expression. Proceedings of the Third International Workshop on CVPR for Human Communicative Behavior Analysis (CVPR4HB 2010), San Francisco, USA, 94-101.