APCVAug 8, 2018

Pattern Recognition Approach to Violin Shapes of MIMO database

arXiv:1808.02848v11 citations
Originality Synthesis-oriented
AI Analysis

This addresses the lack of statistical analysis in violin morphology for music historians and instrument researchers, though it is incremental as it applies existing methods to new data.

The study tackled the problem of characterizing violin shape evolution over time by analyzing images from the MIMO database, finding that the average violin outline has remained mostly stable without significant design trends across historical periods.

Since the landmarks established by the Cremonese school in the 16th century, the history of violin design has been marked by experimentation. While great effort has been invested since the early 19th century by the scientific community on researching violin acoustics, substantially less attention has been given to the statistical characterization of how the violin shape evolved over time. In this paper we study the morphology of violins retrieved from the Musical Instrument Museums Online (MIMO) database -- the largest freely accessible platform providing information about instruments held in public museums. From the violin images, we derive a set of measurements that reflect relevant geometrical features of the instruments. The application of Principal Component Analysis (PCA) uncovered similarities between violin makers and their respective copyists, as well as among luthiers belonging to the same family lineage, in the context of historical narrative. Combined with a time-windowed approach, thin plate splines visualizations revealed that the average violin outline has remained mostly stable over time, not adhering to any particular trends of design across different periods in music history.

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