Move Match: Live Dance Motion Monitoring and Feedback System

Dance movement accuracy prediction is a critical component of modern dance training, yet traditional methods often lack objectivity due to the subjective nature of evaluations and the complexity of human movement. To address these challenges this paper introduces MoveMatch, which is a web-based platform built for real-time dance movement prediction. By leveraging deep learning techniques, the platform performs posture estimation in real-time and detects key points. The system compares the detected poses using Euclidean distance to calculate the alignment between corresponding key points which provides a quantitative measure of the user's accuracy. Based on this comparison, MoveMatch delivers real-time feedback, offering an accuracy score and personalized suggestions for improvement. This immediate feedback fosters a more efficient and engaging learning experience for dancers. Extensive testing of MoveMatch in various dance styles demonstrates its effectiveness in objectively assessing performance, enhancing both training quality and accessibility. The integration of pose estimation, deep learning and real-time comparison offers a novel, user-friendly solution for dancers seeking to improve their skills, transforming traditional dance education with AIdriven insights.