Face Emotion Recognition based Recommendation System

Authors

  • Mareeswari V Associate Professor, Visvesvaraya Technological University (VTU), India
  • Sriharsha. V Computer Science and Engineering, ACS College of Engineering, Bangalore, India
  • Praveen Kumar Computer Science and Engineering, ACS College of Engineering, Bangalore, India
  • Rohith S Computer Science and Engineering, ACS College of Engineering, Bangalore, India
  • Rudra Pratap Singh Computer Science and Engineering, ACS College of Engineering, Bangalore, India

DOI:

https://doi.org/10.34293/acsjse.v2i1.29

Abstract

Face recognition technology has gotten a lot of press because of its wide range of applications and market potential. It is used in a variety of fields, including surveillance systems, digital video editing, and other technical advancements. In the fields of tourism, music, video, and film, these systems have overcome the burden of irrelevant knowledge by taking into account user desires and emotional states. Advice systems, emotion recognition, and machine learning are proposed as thematic categories in the analysis. Our vision is to develop a method for recommending new content that is based on the emotional reactions of the viewers. Music is a form of art that is thought to have a stronger connection to a person's emotions. It has the unique potential to boost one's mood, and video streaming services are becoming more prevalent in people's lives, necessitating the development of better video recommendation systems that respond to their users in a customised manner. Furthermore, many users will believe that travel would be a method to help them cope with their ongoing emotions. Our project aims to create a smart travel recommendation system based on the user's emotional state. This project focuses on developing an efficient music, video, movie, and tourism recommendation system that uses Facial Recognition techniques to assess the emotion of users. The system's overall concept is to identify facial expression and provide music, video, and movie recommendations based on the user's mood.

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Published

2022-03-08

Issue

Section

Articles