Real-Time Emotion Recognition System using Facial Expressions and Soft Computing methodologies

S.Arun Inigo; V.Rajesh Kumar; P.Ashokram

Author:

S.Arun Inigo, V.Rajesh Kumar, P.Ashokram

Published in

Journal of Science Technology and Research

( Volume , Issue )

Page No: 1 - 14

Volume , Issue

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Abstract

Facial Expression conveys non-verbal cues, which plays an important role in interpersonal relations. The Cognitive Emotion AI system is the process of identifying the emotional state of a person. The main aim of our study is to develop a robust system which can detect as well as recognize human emotion from live feed. There are some emotions which are universal to all human beings like angry, sad, happy, surprise, fear, disgust and neutral. The methodology of this system is based on two stages- facial detection is done by extraction of Haar Cascade features of a face using Viola Jones algorithm and then the emotion is verified and recognized using Artificial Intelligence Techniques. The system will take image or frame as an input and by providing the image to the model the model will perform the preprocessing and feature selection after that it will be predict the emotional state.

Keywords

Emotional Quotient, Emotional Intelligence, Ethnicity.

References

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ABSTRACT:

Facial expressions are powerful non-verbal cues that play a vital role in human communication. This research focuses on developing a Real-Time Facial Expression Recognition system using Cognitive Emotion AI to detect and classify emotional states from live video feeds. The system is designed to recognize seven universal human emotions: happiness, sadness, anger, surprise, fear, disgust, and neutral. The methodology involves two major phases—facial detection using Haar Cascade classifiers with the Viola-Jones algorithm and emotion classification using advanced AI techniques. After capturing a video frame or image, the model performs preprocessing and feature extraction to prepare the data for classification. The AI model then predicts the emotional state with high accuracy. This system has potential applications in healthcare, education, security, and human-computer interaction by providing machines the ability to interpret human emotions . Our goal is to bridge the gap between artificial intelligence and emotional intelligence for more empathetic technology.

INTRODUCTION:

Facial expressions are among the most immediate and natural ways for humans to communicate feelings and intentions. In many environments—such as hospitals, classrooms, or customer service—individuals may suppress or struggle to express emotions. In such cases, a machine capable of accurately identifying emotions can support better communication. The advancement of Artificial Intelligence (AI) has enabled machines to perform complex tasks involving analysis and decision-making. However, traditional AI systems are strong in logic and computation (IQ) but often lack Emotional Intelligence (EQ). To address this limitation, we propose a Real-Time Facial Expression Recognition system using Cognitive Emotion AI. This system empowers machines to detect, interpret, and respond to human emotions . By integrating computer vision with machine learning, it can analyze facial cues effectively and intuitively. As technology becomes more integrated into our daily lives, emotionally aware AI ensures that human connection remains a core component of digital interaction.

Real-Time Emotion Recognition System using Facial Expressions and Soft Computing methodologies