This repository contains demo and files in order to easily build and run an Emotion Recognition classifier. This model was trained using three popular datasets: CK+ [1], Bosphorus [2] and RafD [3]. Training procedure is not supplied, but I can do it for sure if it is required.
- demo.ipynb
- ./demo.py
[1] Lucey, P., Cohn, J. F., Kanade, T., Saragih, J., Ambadar, Z., & Matthews, I. (2010, June). The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression. In Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on (pp. 94-101). IEEE.
[2] Savran, A., Alyüz, N., Dibeklioğlu, H., Çeliktutan, O., Gökberk, B., Sankur, B., & Akarun, L. (2008). Bosphorus database for 3D face analysis. Biometrics and identity management, 47-56.
[3] Langner, O., Dotsch, R., Bijlstra, G., Wigboldus, D. H., Hawk, S. T., & Van Knippenberg, A. D. (2010). Presentation and validation of the Radboud Faces Database. Cognition and emotion, 24(8), 1377-1388.