mlsanityData to 14 Oct 2026

From Elevation Maps To Contour Lines: SVM and Decision Trees to Detect Violin Width Reduction

arXiv 2604.02446 ↗First posted 2 Apr 2026cs.CV cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 7 references that are in the map. First posted on arXiv 2 Apr 2026.

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References · 5

  1. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
  2. 2017Deep Setscited by 1,421
  3. 2022Validation of a photogrammetric approach for the objective study of ancient bowed instrumentscited by 3
  4. 2024A discussion about violin reduction: geometric analysis of contour lines and channel of minimacited by 2
  5. 2025Identification of Violin Reduction via Contour Lines Classificationcited by 1

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