Algorithm turns computers into art experts. Making broad differentiations between modern and classic paintings can be fairly easy for the untrained eye, but telling the difference between an Impressionist and a Post-Impressionist painting may require a certain knowledge of art history.
Well, it ain’t necessarily so when it comes to computers. An algorithm created and tested by computer scientists Lior Shamir and Jane Tarakhovsky, of Lawrence Technological University in Michigan has produced surprisingly accurate and expert results in art analysis. The experiment was performed on approximately 1,000 paintings by celebrated artists. The technique is based on numerical image context descriptors, 4,027 of which were computed from each painting. These are numbers that identify the content of the image such as texture, color and shapes. The algorithm succeeded in producing a network of similarities between painters that was largely consistent with the analysis that an art history expert would make. View gallery - 2 images. A Sci-Film Written Entirely by an AI Computer. Every text message or email you’ve ever typed into your smartphone has been read and analyzed by AI software.
This is how our devices have become so creepily good at auto-completing (and sometimes, auto-butchering) our texts and emails. But what would happen if that same AI turned its focus away from our personal messages, and instead studied movie and TV scripts? What would it learn, and what would it try to create? Computer creates high-tech Rembrandt counterfeit. In conversations about artificial intelligence and the time when machines will be able to functions as well as — or better than — human beings, it's often said that one thing computers will never be able to do is create art and music the way we do.
Well, that argument just lost a bit of steam thanks to a project that's been carried out by Microsoft and ING. Working with the Technical University of Delft and two museums in the Netherlands, the project, called "Next Rembrandt," used algorithms and a 3D printer to create a brand-new Rembrandt painting that looks like it could easily have been delivered by Dutch Master's own hand about 350 years ago. What do machines sing of? « Martin Backes – Official Website. „What do machines sing of?
“ is a fully automated machine, which endlessly sings number-one ballads from the 1990s. As the computer program performs these emotionally loaded songs, it attempts to apply the appropriate human sentiments. This behavior of the device seems to reflect a desire, on the part of the machine, to become sophisticated enough to have its very own personality. What do machines sing of? (90s Version) 2015 Size: 170 x 55 x 45 cm Material: metal stand, mic stand, mic, cable, 2 screens, computer, custom-made computer program List of songs which are included and performed by the computer program: Whitney Houston – I Will Always Love You R. I also uploaded the video to YouTube. A big thanks goes to Prof. The work has been created at the University of Arts in Berlin (Art and Media Departement) with the environment and programming language SuperCollider.
How computers experience art. If you ask a computer to describe a piece of abstract art, it might tell you a priceless print looks like a toilet.
To better understand how algorithms interpret art that even humans might not fully understand the meaning of, artist and researcher Matthew Plummer-Fernandez started a blog called “Novice Art Blogger,” in which a computer experiences art for the first time. His code randomly selects an abstract piece of artwork from the Tate online archive and then sends the picture to an image-classification algorithm.
The deep learning algorithm was created by researchers at the University of Toronto, and they’ve made their work available publicly for anyone to use. The algorithm looks at images and tries to translate them into text captions based on what it sees. To teach the software to recognize different shapes, actions, or colors, researchers provide pre-captioned data with descriptions of each image, and the computer compares the new images to the ones already in its system.
INTERESTING.JPG (@INTERESTING_JPG) Machine Learning Algorithm Studying Fine Art Paintings Sees Things Art Historians Had Never Noticed — The Physics arXiv Blog. The task of classifying pieces of fine art is hugely complex.
When examining a painting, an art expert can usually determine its style, its genre, the artist and the period to which it belongs. Art historians often go further by looking for the influences and connections between artists, a task that is even trickier. So the possibility that a computer might be able to classify paintings and find connections between them at first glance seems laughable. And yet, that is exactly what Babak Saleh and pals have done at Rutgers University in New Jersey. These guys have used some of the latest image processing and classifying techniques to automate the process of discovering how great artists have influenced each other.
The way art experts approach this problem is by comparing artworks according to a number of high-level concepts such as the artist’s use of space, texture, form, shape, colour and so on. So Saleh and co experiment with a number of different metrics. That is interesting stuff.