Optimization Based Framework for the Classification of Human Emotion in Facial Images

By MR C Agilan

People's daily lives are heavily reliant on communication. When humans communicate with one another, they display a variety of emotions. Recognizing emotions is a fascinating and difficult undertaking. Text, speech, facial expressions, gestures, and biological signals can all be used. Affective computing and technology have grown increasingly crucial in understanding human behavior during the last decade. Patient monitoring, driver fatigue detection, robotics, animation, forensics, medical aid, psychology, surveillance, automotive industry, Human-Robot Interaction for children with autism, situation analysis of social interaction, affective computing, feedback during E-Learning, psychology, contests, and entertainment industries have all benefited from emotion recognition research. Many academics have been driven in recent days to construct an innovative and robust generic and application-specific affective computing system in conjunction with Emotion Intelligence.

Emotion is a strong, subjective, and changing feeling state that communicates the importance of good or negative stimuli. The physical cause of emotion origin in the human brain must be investigated. Robots are stimulated in the same way since they are supposed to work in an environment and be able to engage with humans on an emotional level. Important variables include social learning, gesture and natural language communication, emotion perception, and synthesis of interacting partners.

• Format: Paperback
• Language: English
• ISBN: B0CVQKNGDJ
• ISBN13: 9798224420742
• Release Date: February 2024
• Publisher: Mohammed Abdul Malik
• Length: 182 Pages
• Weight: 0.96 lbs.
• Dimensions: 0.4" x 8.5" x 11.0"