Curating Emotion-Based Music Playlists with CNN and Haar Cascade for Facial and Eye Detection
摘要
Music has consistently been recognized for its emotional value and unique capacity to improve mood. Because of the fast-paced nature of today’s world and rising stress levels, music has become a vital part of people’s daily lives to relax. By creating playlists based on user emotions, the proposed work improves the listening experience. Face recognition, feature extraction, mood detection, and music recommendation are the four main steps in the process. A personalized playlist based on the detected emotion reflects the user’s preferred songs and current mood. The recommended playlist is shown on the right side of the video frame, while the user’s emotion will be identified through real-time video recording. This method combines real-time emotion detection with music recommendation using Haar cascade with frontal face and eye classifier to provide tailored user experiences, efficient stress relief, and an improved listening experience.