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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.19548187 |
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| _version_ | 1866902306242428928 |
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| author | Al Bulushi, Mazin Al Busaidi, Abdulaziz |
| author_facet | Al Bulushi, Mazin Al Busaidi, Abdulaziz |
| contents | <p>This project presents a vision-based piano learning assistant that uses computer vision techniques to detect key presses from video input and provide real-time feedback through a gamified “falling notes” interface. Implemented on a Raspberry Pi, the system combines perspective correction, key segmentation, and skin tracking to achieve accurate detection while filtering noise such as shadows and reflections. A two-phase pipeline ensures high performance and smooth visualization, achieving around 93% accuracy and enabling an interactive and engaging piano learning experience.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19548187 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | The Piano Tutor: Design and Implementation of a Novel CV-based Piano Learning System Al Bulushi, Mazin Al Busaidi, Abdulaziz <p>This project presents a vision-based piano learning assistant that uses computer vision techniques to detect key presses from video input and provide real-time feedback through a gamified “falling notes” interface. Implemented on a Raspberry Pi, the system combines perspective correction, key segmentation, and skin tracking to achieve accurate detection while filtering noise such as shadows and reflections. A two-phase pipeline ensures high performance and smooth visualization, achieving around 93% accuracy and enabling an interactive and engaging piano learning experience.</p> |
| title | The Piano Tutor: Design and Implementation of a Novel CV-based Piano Learning System |
| url | https://doi.org/10.5281/zenodo.19548187 |