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How AI helps unlock the secrets of Old Master and modernist paintings, Ars Technica

How AI helps unlock the secrets of Old Master and modernist paintings, Ars Technica


      On the third day of Christmas –


Two recent papers offer innovative twists on machine learning as applied to art.


          -Dec 150, 2560 1: (UTC UTC) **************   **************************         

**************************************Restorers of the Royal Institute for Cultural Heritage remove surpeints and reveal the original of the “Adoration of the Mystic Lamb” altarpiece by the Van Eyck brothers.

X-rays are awell-established tool

to help analyze and restore valuable paintings because the rays’ higher frequency means they pass right through paintings without harming them . X-ray imagingcan reveal anything

Picasso’sThe Old Guitaristis one of the best- known works from the artist’s so-called “Blue Period.” Two decades ago, X-ray and infrared analysis revealed that he had re-used an older canvas (a common practice for struggling artists of the period). There was another painting underneath, of a seated woman, that matched a sketch Picasso had included in a letter to a friend. But the X-ray and infrared images couldn’t provide sufficient detail to get a sense of what the original painting really looked like, especially the choice of colors.

In a paper posted to the physics arXiv

in September, Anthony Bourached and George Cann of the University College London described how they employed machine learning to reconstruct a full-color image of Picasso’s original underpainting — specifically, a technique called neural style transfer,originally developeda few years ago by researchers at the University of Tübingen in Germany. Per Technology Review:Neural networks consist of layers that analyze an image at different scales. The first layer might recognize broad features like edges, the next layer sees how these edges form simple shapes like circles, the next layer recognizes patterns of shapes, such as two circles close together, and yet another layer might label these pairs of circles as eyes .

this kind of network would be able to recognize eyes in paintings in a wide variety of styles, from Leonardo da Vinci to Van Gogh to Picasso. In each case, the eyes form a similar pattern that the machine can pick out.

The network can also be trained to recognize distinctive styles, telling the difference between a Picasso and, say, a Van Gogh painting , for instance. It’s also possible to reverse the process: give the neural network an image, and then superimpose a given style onto it.

 Visual method of reconstructing the art beneath Picasso's  The Old Guitarist<a data-height=. ” height=”448 “src=” / / the-seated-woman_1 – (x) ****************************************************************************************************. png “width=” 648**********************

Enlarge /Visual method of reconstructing the art beneath Picasso’sThe Old Guitarist **************** A. Bourached and G.H. Cann

That’s what Bourached and Cann did with the X-ray image of the painting underThe Old Guitarist(They also applied the technique to another Picasso canvas to reconstruct an underpainting done by Spanish painter Santiago Rusinol.) It may or may not be how Picasso chose to paint it, but the process is still useful for gaining a better understanding of subjective human creativity . “Our method of combining original but hidden artwork, subjective human input, and neural style transfer helps to broaden an insight into an artist’s creative process,” the authors wrote.Illuminating a medieval masterpieceAI techniques are also proving useful in art conservation efforts. The Ghent altarpiece — aka theAdoration of the Mystic Lamb – is a

************************************************************************************** th-century polyptych attributed to brothers Hubert and Jan van Eyck , displayed in the Saint Bavo Cathedral in Belgium. Originally consisting of 15 panels, the altarpiece features two “wings” of four panels each, painted on both sides. Those wings were opened on church feast days so congregants could view the interior four central panels. The inner upper register features Christ the King, the Virgin Mary, and John the Baptist, flanked by the outer panels depicting angels and the figures of Adam and Eve. The inner lower register depicts John the Baptist and St. John the Evangelist, with a group of saints, sinners, clergy, and soldiers in between.
The Museum of Fine Arts in Ghent began restoring the altarpiece in October, allowing the public to view the process from behind a glass screen as conservators from the Royal Institute for Cultural Heritage worked on individual panels. The restoration also produced a series of high-resolution images of the various panels using different imaging techniques.

Those images in turn formed the basis for an investigation into applying AI analysis to the altarpiece images by researchers at Duke University, the National Gallery, and University College London. The team reported on their work in a paperfor Science Advances. “They have one of the most famous paintings in the world, and they are willing to work with us,” co-author Ingrid Daubechies of Duke University told Ars. “It’s a great situation.”