Facial Expression Recognition

The main purpose of the project is recognition of emotions based on facial expressions. Cohn-Kanade data set (http://www.pitt.edu/~emotion/ck-spread.htm) is used for explorations and training.

The Cohn-Kanade dataset of face images labeled for 7 expressions/emotions :

• Anger
• Contempt
• Disgust
• Fear
• Happiness
• Sadness
• Surprise

The solution consists of versatile classifiers including Decision Tree, Random Forests, Support Vector Machines, DT based Binary Classifier, simple hybrid classifier.

Performance results, estimated by cross validation tests:

• Multi-class Support Vector Machines (radial kernel, kernlab): 97.3% (st. deviation = 0.4%)
• Multi-class Support Vector Machines (linear kernel, e1071): 96.5%
• Decision Tree based classifier: 89.63%

GNU GENERAL PUBLIC LICENSE