1 Automation and Process Control Engineer, Gist Limited, Bristol, United Kingdom.
2 Mechanical Engineering Department Teesside University, United Kingdom.
3 Electrical Engineer, University of South Wales, United Kingdom.
4 Data Analyst, Emporia State University, United States.
World Journal of Advanced Research and Reviews, 2024, 23(01), 2599–2620
Article DOI: 10.30574/wjarr.2024.23.1.2258
DOI url: https://doi.org/10.30574/wjarr.2024.23.1.2258
Received on 13 June 2024; revised on 24 July 2024; accepted on 26 July 2024
This study proposes an advanced real-time mood prediction system that utilizes Convolutional Neural Networks (CNNs) and webcam-based Region of Interest (ROI) extraction. By employing MATLAB and its Computer Vision Toolbox, the system detects and preprocesses facial regions from live webcam feeds to accurately predict an individual’s mood. The performance of this system is validated using a custom dataset, showcasing its potential for applications in human-computer interaction, psychological assessments, and real-time monitoring. This approach highlights a significant advancement in combining AI and image processing for real-time emotional analysis.
Convolutional Neural Networks (CNNs); Real-time mood prediction; Region of Interest (ROI) extraction; Webcam-based detection; MATLAB; Computer Vision Toolbox
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Joseph Nnaemeka Chukwunweike, Damilola Adebayo, Abiodun Anuoluwapo Agosa and Nana Osei Safo. Implementation of MATLAB image processing and AI for real-time mood prediction. World Journal of Advanced Research and Reviews, 2024, 23(01), 2599–2620. Article DOI: https://doi.org/10.30574/wjarr.2024.23.1.2258
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0