This paper tends to design an artificially intelligent system capable of emotion recognition through facial expressions of
unknown people. The network in this paper consists of three convolutional layers each followed by max pooling and ReLU. The
network is trained on FER2013 dataset and tested on RaFD dataset thus giving a wide range of training images to the network, so
that it can overcome the basic problem of recognition of unknown faces. The pertinence of the final model is depicted in a live
video application that can instantaneously return users emotions based on their facial posture. The accuracy obtained by this
method was 68%, which is better than the previous state-of-the-arts methods. The results provide an important insight on the
significance of using different datasets for training and validation.
