An Intelligent Mobile Application to Analyze Dance Movements and Provide Feedbacks using Media Pipe and OpenCV

Abstract

Motion Mentor is a mobile application designed to address a challenge faced by beginner dancers in improving their dancing technique-the development of improper movements and habits when practicing without a teacher’s guidance. Therefore, Motion Mentor offers real-time posture correction and personalized feedback [5]. This method involves using the Mediapipen pose-detection AI model for real time posture detection, combined with advanced algorithms for accurate dance analysis, and Firebase for the storage of data and uploaded videos [6]. Users can access educational content, record their dance performances for feedback, and review their progress. During the experimentation, our system was applied to scenarios involving rapid dance movements to test the accuracy of pose estimation, comparison between the estimated and the actual real-time distance and speed estimation [7]. These scenarios suggested the limitations of our application in different dynamic and lighting conditions, providing insights into areas for improvement. Overall, this solution enhances accessibility and conveniences for all dancers in improving dance technique, offering real-time feedback and educational materials.