Real Time Emotion Detection Using Deep Learning

Facial expressions depict emotions and produce information on the personalities and thoughts of people. The machine performs different tasks constantly in order to increase its use in public. Machines that are able to understand emotions can be used to execute a wide range of tasks. Machine perception demands machines to grasp information about their environment. The understanding of human facial expressions is a key component to understand emotions and also to find broad applications in the field of human-computer interaction. Tensorflow framework, Keras library and the Xception Architecture of CNN are used to train the model on the Fer2013 dataset.