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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2604.02446 |
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| _version_ | 1866914441792061440 |
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| author | Beghin, Philémon Ceulemans, Anne-Emmanuelle Glineur, François |
| author_facet | Beghin, Philémon Ceulemans, Anne-Emmanuelle Glineur, François |
| contents | We explore the automatic detection of violin width reduction using 3D photogrammetric meshes. We compare SVM and Decision Trees applied to a geometry-based raw representation built from elevation maps with a more targeted, feature-engineered approach relying on parametric contour lines fitting. Although elevation maps occasionally achieve strong results, their performance does not surpass that of the contour-based inputs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_02446 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | From Elevation Maps To Contour Lines: SVM and Decision Trees to Detect Violin Width Reduction Beghin, Philémon Ceulemans, Anne-Emmanuelle Glineur, François Computer Vision and Pattern Recognition Artificial Intelligence We explore the automatic detection of violin width reduction using 3D photogrammetric meshes. We compare SVM and Decision Trees applied to a geometry-based raw representation built from elevation maps with a more targeted, feature-engineered approach relying on parametric contour lines fitting. Although elevation maps occasionally achieve strong results, their performance does not surpass that of the contour-based inputs. |
| title | From Elevation Maps To Contour Lines: SVM and Decision Trees to Detect Violin Width Reduction |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2604.02446 |