Real-Time Facial Emotion Detection Using Machine Learning

In recent years, the advancements in Machine Learning (ML) and Computer Vision (CV) techniques have facilitated the development of “Real-time Facial Emotion Detection” systems. These platforms find utility in a range of domains, encompassing human-computer Engagement, psychology, and human emotion analysis and provides a novel approach for “Real-time Facial Emotion Detection Using Machine Learning” (RFEDUML) algorithms. The proposed system utilizes ML functionalities, particularly “Convolutional Neural Networks” (CNNs), to analyze and classify facial emotions from live pictures.

I. Introduction

Crucial aspect also a fundamental feature of human communication and convey rich information about a person's emotions, intentions, and mental states. Detecting and interpreting facial emotions accurately and in real-time has become a significant diverse field with multiple utilization in realms like human-computer interaction, psychological science, and social robotics. Recent advancements in ML and “Computer Vision” (CV) techniques have led to development of robust and efficient systems for “Real-time Facial Emotion Detection Using Machine Learning” (RFEDUML).