Real-time Emotion Detection

Abstract

8 emotions detected in real-time with ~77% accuracy. Used: OpenCV, Python 3, Keras, Data Preprocessing, Deep Learning & Machine learning Techniques.

Build

You can build the project by executing following bash file:

./build.sh

Build instructions are provided for Linux only, you can use the equivalent commands for other operating-systems.

Note that, if you have trouble with installing dllib library, you can check out the link.

Run

After build, you can enter the following command in your Linux Terminal to run the program:

./run_all.sh

Note that, you will get emotion detection results live and periodically. You can run "main.py" with "python3" if you want to see the emotion detection results in console.

Dataset

Name: Cohn-Kanade (CK and CK+) Dataset

Source: http://www.consortium.ri.cmu.edu/ckagree/

Contributors

• Berk Sudan, GitHub, LinkedIn
• İrem Şahin, GitHub, LinkedIn

References

• Facial landmarks with dlib, OpenCV, and Python: https://www.pyimagesearch.com/2017/04/03/facial-landmarks-dlib-opencv-python/
• 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.