Next time you go on vacation, you may want to think twice before shooting hundreds of photos of that scenic mountain or lake.
A new study from MIT neuroscientists shows that the most memorable photos are those that contain people, followed by static indoor scenes and human-scale objects. Landscapes? They may be beautiful, but they are, in most cases, utterly forgettable.
“Pleasantness and memorability are not the same,” says MIT graduate student Phillip Isola, one of the lead authors of the paper, which will be presented at the IEEE Conference on Computer Vision and Pattern Recognition, taking place June 20-25 in Colorado Springs.
The new paper is the first to model what makes an image memorable — a trait long thought to be impenetrable to scientific study, because visual memory can be so subjective. “People did not think it was possible to find anything consistent,” says Aude Oliva, associate professor of cognitive science and a senior author of the paper.
However, the MIT team, which also included Antonio Torralba, the Esther and Harold E. Edgerton Associate Professor of Electrical Engineering and Computer Science, and one of his graduate students, Jianxiong Xiao, was surprised to see remarkable consistency among hundreds of people who participated in the memory experiments.
Can you guess which of these images would be the most memorable? Give up? It’s the top left and bottom right ones.
Images courtesy of the Oliva and Torralba labs
Using their findings from humans, the researchers developed a computer algorithm that can rank images based on memorability. Such an algorithm could be useful to graphic designers, photo editors, or anyone trying to decide which of their vacation photos to post on Facebook, Oliva says.
Why we remember
Oliva’s previous research has shown that the human brain can remember thousands of images, with a surprising level of detail. However, not all images are equally memorable.
For the new study, the researchers built a collection of about 10,000 images of all kinds — interior-design photos, nature scenes, streetscapes and others. Human subjects in the study (who participated through Amazon’s Mechanical Turk program, which farms tasks out to people sitting at their own computers) were shown a series of images, some of which were repeated. Their task was to indicate, by pressing a key on their keyboard, when an image appeared that they had already seen.
Each image’s memorability rating was determined by how many participants correctly remembered seeing it.
In general, different research subjects tended to produce similar memorability ratings. “There are always differences between observers, but on average, there is very high consistency,” says Oliva, who is also a principal investigator in the computer vision group at MIT’s Computer Science and Artificial Intelligence Laboratory.
After gathering their data, the researchers made “memorability maps” of each image by asking people to label all the objects in the images. A computer model can then analyze those maps to determine which objects make an image memorable.