Abstract

Author:
Rajendra Kumar, Masanori Fukui, Aman Anand

Doi: 10.26480/mmhj.02.2024.60.63

This is an open access article distributed under the Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Emotion recognition or identification is one of the most complicated domains in the field of artificial intelligence and data science. Much important research work has been done on emotion identification. The primary challenge in emotion identification is the different features in the facial image and the appropriate choice of technique. In this review paper, the recent work on emotion identification and different issues related to emotion identification have been compared and analyzed. The study explores the potential of thermal imaging and anatomical parameters to enhance emotion recognition systems. This multi-faceted approach has implications for healthcare system and well-being, marketing and customer service, entertainment and gaming, automotive industry, personal devices and wearable, security, emotion analysis,and education, offering new insights and applications. In this research paper we have provided detail analysis of technique such as YOLOv3, YOLOv5 and CNN for the emotion identification.