Beauty Now in the Eye of the Algorithm

New technology from Xerox can sort photos not just by their content but also according to their aesthetic qualities, such as which portraits are close-in and well-lit, or which wildlife shots are least cluttered.
Still in the prototype stage, the technology could eventually help with tasks like choosing which of hundreds of digital photos taken on a family vacation should appear in a photo album. It could help stock agencies sort photos by their characteristics, and it could be deployed inside a camera to help people delete lower-quality scenes quickly, saving on storage space and hassle.

"What they show is that now you don't need a human to select images that are going to be judged beautiful," says Aude Olivia, an associate professor of brain and cognitive sciences at MIT, who also works on image recognition. "You can run the algorithm, and it will give a good estimate."
The technology—developed at the Xerox Research Center Europe in Grenoble, France—is slated for beta testing with Xerox corporate partners next year, says Craig Saunders, manager of the computer vision research group there. These partners include graphic design firms, online photo-book companies, and stock agencies, all of which might want new ways to sort and find photos.

The Xerox system learns about quality photography by studying photos that had previously been chosen for public display in online photo albums, such public ones shown on Facebook, or photos tagged as high quality on Flickr. Then it notes common characteristics of these photos.
Not surprisingly, these characteristics often correspond to what experts already understand about good photographs. The best portraits of people, for example, have indirect lighting and blurry or monochromatic backgrounds that help keep the focus on the person. Good beach photos often include silky-looking waves, a trick achieved through slow shutter speeds. And many kinds of photos are appealing because they follow the "rule of threes," with subjects divided among three zones in the photo. "We try to learn what it is about these features that makes photos 'good,'" says Saunders. (Examples and demonstrations can be found here.)