Try to visualize Paris. If you are like me, you will imagine a tourist-guidebook composite—the Eiffel Tower lit up at night, the Notre Dame Cathedral, the bridges over the Seine, and so on. But this is not what most of Paris looks like. It turns out that many people can look at a photograph of any randomly selected street corner in Paris, and can correctly identify the city with high accuracy, even without paying attention to any text in the photo. One must conclude that all of Paris is infused with a "Paris-ness"—a certain je ne sais quoi—that leaves an indelible visual mark on the City of Light.
How can we quantify this Parisness? Can a computer automatically discover and tell us what makes Paris look so much like Paris? More broadly, this question of visual style is an important one in computer graphics and vision. Identifying the key elements that characterize a style—whether a style of interior design, art, or, in the case of a city, its architecture and ornamentations—could aid in a range of applications, such as obtaining reference imagery for a new design task, or for summarizing or categorizing the look of a large set of images.