Abstract
Learning to interpret sheet music and play musical instruments (piano) remains a significant challenge for beginners, often requiring extensive practice and guidance. Existing platforms lack real-time feedback and seamless sheet music interpretation, creating inefficiencies that require a system for accurate note recognition, intuitive guidance, and reduced cognitive load. To address this, we propose a novel system that integrates optical music recognition (OMR) and virtual reality (VR) to create an immersive piano learning environment. The proposed approach improves the detection of musical notes by making it scale and rotation invariant. The detected notes are converted into the corresponding piano keys and sequential instructions. These instructions are then visualized in a VR environment in Meta Quest 3, where a virtual piano highlights keys dynamically to guide the user. The experimental results demonstrate high accuracy in note detection and significant improvements in the learning curve for beginners, reducing cognitive load, and bridging the gap between sheet music interpretation and piano playing. This work highlights the potential of combining document image analysis and VR technologies to revolutionize music education, as well as other related fields, offering a scalable and accessible solution.
| Original language | English |
|---|---|
| Title of host publication | Document Analysis and Recognition – ICDAR 2025 - 19th International Conference Wuhan, China, September 16–21, 2025 Proceedings, Part III |
| Editors | Xu-Cheng Yin, Dimosthenis Karatzas, Daniel Lopresti |
| Place of Publication | Cham Switzerland |
| Publisher | Springer |
| Pages | 22-39 |
| Number of pages | 18 |
| ISBN (Electronic) | 9783032046246 |
| ISBN (Print) | 9783032046239 |
| DOIs | |
| Publication status | Published - 2026 |
| Event | International Conference on Document Analysis and Recognition (ICDAR) 2025 - Wuhan, China Duration: 16 Sept 2025 → 21 Sept 2025 Conference number: 19th https://link.springer.com/book/10.1007/978-3-032-04624-6 (Proceedings) https://www.icdar2025.com/ (Website) |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Publisher | Springer |
| Volume | 16025 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | International Conference on Document Analysis and Recognition (ICDAR) 2025 |
|---|---|
| Abbreviated title | ICDAR 2025 |
| Country/Territory | China |
| City | Wuhan |
| Period | 16/09/25 → 21/09/25 |
| Internet address |
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Keywords
- Document Recognition
- Immersive Learning
- Music Education
- Optical Music Recognition
- Symbol spotting
- Virtual Reality
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