Emotion Recognition System from Facial Expressions Using Machine Learning
Year: 2025
Type: article
Abstract: Facial Emotion Recognition (FER) enables automatic classification detection of human emotions from facial expressions using deep learning (DL) and computer vision techniques. In this paper, a hybrid real-time emotion recognition system using Convolutional Neural Networks (CNNs), OpenCV, and DeepFace is proposed to achieve accurate and dynamic emotion analysis. The system aims to identify emotions such as happiness, sadness, anger, surprise, and fear with a high level of accuracy to enable enhanced Human-Computer Interaction (HCI), mental health monitoring, and smart safety systems. The method used includes offline training of the model and real-time emotion recognition using video. The technique employs continuous learning and optimization strategies to maximize recognition rates and resilience in practical environments.
Authors: Sneha Taru, Ankita Gursali, Nikita Kedare, Rutuja Dange, Manisha Mehrotra
Language: English
Topic: Emotion and Mood Recognition
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4410682008