This master thesis compares different face descriptors using classification techniques in
order to classify emotions in images of faces of people of different ethnicities and ages,
male and female. The comparison is done between hand-crafted features such as LBP and
HOG and more modern features such as some pre-trained neural networks. The proposed
methods were used on different databases, using different image sizes and cropping and
standardizing all the images. The experimental results showed that some of the hand-
crafted features were better that the pre-trained neural networks. To facilitate replication
of our experiments the MATLBAB source code will be available at https://github.
com/nagwlei/FaceEmotions
