Real-Time Facial Emotion Detection Using OpenCV and CNN with Music Playback System

B. Venkata Charan Kumar, N. Venkatesh Naik, B. Sumanth, N. Mahaboob Hussain, B. Sai Charan, P. M. D. Akram

2025

Abstract

Contemporary human-computer interfaces increasingly demand affective computing capabilities to interpret user states. This research presents an innovative framework combining computer vision techniques with deep learning to achieve real-time facial emotion analysis, subsequently driving an intelligent music recommendation engine. Our architecture employs OpenCV for facial feature extraction and a custom convolutional neural network for emotion classification, achieving 91% accuracy under optimal conditions. The integrated music subsystem utilizes audio feature extraction and sentiment analysis to dynamically select contextually appropriate tracks. Comprehensive testing reveals significant improvements in user engagement metrics (20% enhancement) and system responsiveness (45% latency reduction post-optimization). Future directions include implementing transformer architectures for improved micro-expression recognition and developing federated learning approaches to address privacy concerns. This work bridges critical gaps between affective computing and personalized media delivery systems.

Paper Citation

in Harvard Style

Kumar B., Naik N., Sumanth B., Hussain N., Charan B. and Akram P. (2025). Real-Time Facial Emotion Detection Using OpenCV and CNN with Music Playback System. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 337-343. DOI: 10.5220/0013882700004919

in Bibtex Style

@conference{icrdicct`2525,
author={B. Kumar and N. Naik and B. Sumanth and N. Hussain and B. Charan and P. Akram},
title={Real-Time Facial Emotion Detection Using OpenCV and CNN with Music Playback System},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={337-343},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013882700004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Real-Time Facial Emotion Detection Using OpenCV and CNN with Music Playback System
SN - 978-989-758-777-1
AU - Kumar B.
AU - Naik N.
AU - Sumanth B.
AU - Hussain N.
AU - Charan B.
AU - Akram P.
PY - 2025
SP - 337
EP - 343
DO - 10.5220/0013882700004919
PB - SciTePress