Facial-Emotions-Based Recommendation System Using Deep Learning

The emotions expressed are the feelings that are seen on the face. Emotional factors profoundly influence social intelligence, encompassing decision-making, communication comprehension, and human behavior. A person’s face may reveal a lot about their feelings. According to psychologists, people communicate their feelings more through non-verbal body language and gestures than through spoken words. Facial expressions are non-verbal forms of communication. Neutral, happy, sad, angry, contempt, disgust, fear, and surprise are the eight common facial expressions. Therefore, it is crucial to detect these expressions on the face. This paper aims to present a thorough and detailed analysis of the majority broadly used emotion recognition techniques, that are often used to emotion recognition issues and suggest material based on emotions. The absence of thorough analysis of every potential approach implementation in the body of existing literature serves as our driving force. Next, we provide a snapshot of five application scenarios for health research, which are music recommendations, movie recommendations, training recommendations, articles for improving mental health by physicians, and mental health-related predictions such as anxiety, depression, and mood swings. This project aims to build a digital platform focusing on people’s constantly changing moods, offering a selection of advanced, individually tailored services enabling them to live well in the community as long as feasible.