In this paper we introduce a mathematical method to extract similarities between paintings and music tracks. Our approach is based on the digitalization of both paintings and music tracks by means of finite expansions in terms of orthogonal basis functions (with both Fourier and wavelet bases). The best fit between a specific painting and a sample of music tracks from a given composer is achieved via an L-2 projection upon a finite dimensional subspace. Several examples are provided for the analysis of a collection of works of art by the Italian artist Marcello Morandini. Finally we have developed an original applet that implements the process above and which can be freely downloaded from the site https://github.com/pgerva/playing-paintings.git.

Let the Paintings Play

Cassani D.
2026-01-01

Abstract

In this paper we introduce a mathematical method to extract similarities between paintings and music tracks. Our approach is based on the digitalization of both paintings and music tracks by means of finite expansions in terms of orthogonal basis functions (with both Fourier and wavelet bases). The best fit between a specific painting and a sample of music tracks from a given composer is achieved via an L-2 projection upon a finite dimensional subspace. Several examples are provided for the analysis of a collection of works of art by the Italian artist Marcello Morandini. Finally we have developed an original applet that implements the process above and which can be freely downloaded from the site https://github.com/pgerva/playing-paintings.git.
2026
2026
http://inf.ucv.ro/~ami/index.php/ami/article/view/2412
Wavelets transform; Fourier transform; audio signals; image signals; least-squares projection
Gervasio, P.; Quarteroni, A.; Cassani, D.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2218271
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