Pemanfaatan Mediapipe Body Pose Estimation dan Dynamic Time Warping untuk Pembelajaran Tari Remo

Abstract

Video can be used as a learning medium for various purposes. In this research, the object of study is the movements of the traditional dance "remo." Thus, as a substitute for an absent coach or instructor, videos can take on the role of a dance instructor. However, video communication is one-way between the coach and the learners. Without movement correction, individuals trying to learn remo dance may find it challenging to determine if they are performing the movements correctly. Therefore, the author aims to create a system to assist coaches in correcting the dance movements of their learners. Using the MediaPipe module and the Dynamic Time Warping algorithm, the author developed a system to correct the learners' dance movements. This system can detect deviations from the coach's instructional video and provide notifications about which body angles do not match the coach's video instructions. The system operates by having users upload a video of their dance movements, and then it identifies which movements deviate from the correct remo dance. The accuracy is measured by comparing the angle distances between the master's movements and the test data. If the angle exceeds a predetermined threshold, the movement is considered incorrect. The system's output is validated by the coach, and it achieves 90% accuracy in identifying movement errors in videos. With this accuracy, the system can assist coaches in evaluating their learners' remo dance movements.

Keywords

• mediapipe
• dtw
• tari remo
• computer vision