Implementation of Emotion Based Multifaceted Recommendation System

In recent years, human emotion has become extremely important. Emotion communicates a person's distinctive behaviors, which can take many various forms. This paper, proposed an algorithm to identify emotions based on hand gestures and facial features of people and recommended books, music and quote based on the emotions found. The data collection and dataset using libraries such as numpy, media pipe, and cv2 for emotion identification. Pygame & Tkinter are used to provide music recommendations. Quote and books Api are used to provide the book and quote recommendation. A device like internal camera is used to record hand gestures and facial expressions. On the input face photos, feature extraction is done to identify emotions including happiness, rage, sadness, surprise, etc. The computational time required to produce the findings and the overall cost of the system are both likely to be reduced by our proposed approach, boosting the system's overall accuracy.