FaceFetch: A User Emotion Driven Multimedia Content Recommendation System Based on Facial Expression Recognition

Recognition of facial expressions of users allows researchers to build context-aware applications that adapt according to the users´ emotional states. Facial expression recognition is an active area of research in the computer vision community. In this paper, we present Face Fetch, a novel context-based multimedia content recommendation system that understands a user´s current emotional state (happiness, sadness, fear, disgust, surprise and anger) through facial expression recognition and recommends multimedia content to the user. Our system can understand a user´s emotional state through a desktop as well as a mobile user interface and pull multimedia content such as music, movies and other videos of interest to the user from the cloud with near real time performance.