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@article{178112,
        author = {K. Shiva Kalyan Babu and M. Mahendhar and N. Sai Ram Goud and S. Balakrishna},
        title = {ANALYSIS OF HUMAN EMOTION BASED MUSIC PLAYER USING OPENCV AND DEEP LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {2823-2827},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178112},
        abstract = {This project presents an Emotion-Based Music Player that utilizes deep learning and computer vision to detect a user's emotion in real-time through facial expressions captured via a webcam. By leveraging the Deep Face library for emotion recognition and Open CV for video processing, the system identifies key emotional states happy, sad, angry, and neutral— and responds by playing corresponding music tracks using Py game. To provide a more interactive and insightful experience, the application also includes a mood history tracking feature that logs emotional changes throughout the session. This allows for basic behavioural analysis and paves the way for potential integration with mood-based recommendation systems. A simple and responsive Flask-based web interface enables users to view their current emotion and live video feed simultaneously. This project demonstrates a creative blend of human-computer interaction, affective computing, and real-time data processing, with potential applications in mental health monitoring, personalized entertainment, and adaptive user interfaces.},
        keywords = {},
        month = {May},
        }