Hugh Pickens writes "Researchers have developed a computer algorithm that can rank images based on memorability. They found that in general, images with people in them are the most memorable, followed by images of human-scale space — such as the produce aisle of a grocery store — and close-ups of objects. Least memorable are natural landscapes. Researchers built a collection of about 10,000 images of all kinds for the study — interior-design photos, nature scenes, streetscapes and others, and human subjects who participated through Amazon's Mechanical Turk program were told to indicate, by pressing a key on their keyboard, when an image appeared that they had already seen. The researchers then used machine-learning techniques to create a computational model that analyzed the images and their memorability as rated by humans by analyzing various statistics — such as color, or the distribution of edges — and correlated them with the image's memorability. 'There has been a lot of work in trying to understand what makes an image interesting, or appealing, or what makes people like a particular image,' says Alexei Efros at Carnegie Mellon University. 'What [the MIT researchers] did was basically approach the problem from a very scientific point of view and say that one thing we can measure is memorability.' Researchers believe the algorithm may be useful (PDF) to graphic designers, photo editors, or anyone trying to decide which of their vacation photos to post on Facebook."