A novel online product recommendation system based on face recognition and emotion detection

This paper presents a novel method for online product recommendation using facial image recognition and emotional feedback for online users. The system detects the faces of the users from the live camera stream along with gender identification and product recommendation algorithms for targeting products to the right user. It also uses an emotion detection technique for getting a feedback about the recommended product. The developed system improves user interaction and can be used in online shopping websites and other places where efficient product recommendation methods are required. It also helps to market products more effectively in a user friendly manner.