Video-based lessons are becoming a popular way for distance piano education. However, limited by the fixed camera angle, a video is difficult to tell precise 3D hand posture, which is one of the most essential factors for learning piano. This paper presents a visualization system providing the intuitive discrepancy of hand postures in two piano performance videos. Through a motion capture system, the estimated 3D postures are visualized and discrepancies based on distinct metrics are displayed, integrated with modular functions assisting skill acquisition. A pilot study proves that the proposed visualization can be a supplementary means for only video-based lessons in terms of correcting hand postures and fingering.
CITATION STYLE
Liu, R., Wu, E., Liao, C. C., Nishioka, H., Furuya, S., & Koike, H. (2023). PianoHandSync: An Alignment-based Hand Pose Discrepancy Visualization System for Piano Learning. In Conference on Human Factors in Computing Systems - Proceedings. Association for Computing Machinery. https://doi.org/10.1145/3544549.3585705
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