Why are some photographs remembered and recognized, while others are quickly forgotten? University of Chicago researchers are leveraging artificial intelligence and machine learning to search for an answer—and have developed a free tool that can predict how likely you are to remember a photo.
Called “ResMem,” the state-of-the-art tool is the most accurate and sophisticated software of its kind. Created by graduate student Coen Needell and Asst. Prof. Wilma Bainbridge in the Department of Psychology, their work builds on recent scientific advances toward identifying the factors that make some images more memorable than others. Their findings were described in a preprint paper released May 25.
ResMem allows anyone to upload photos and receive a “memorability score” between 0 and 1: A score of 0.85, for example, means that 85% of people viewing the image would remember having seen it. Because human memories tend to be fairly good, the average score is higher than 0.5—about 0.756.
“Memorability can be thought of as an intrinsic property to images,” said Bainbridge, an expert on memory. “It is actually something that a computational model can measure, predict and—eventually—maybe even manipulate.”
ResMem can computationally score the memorability of any photograph in a generalizable way. The tool leverages a model built on two datasets from earlier experiments, in which thousands of participants viewed about 70,000 total images and reported what they remembered.
The two datasets used to train the model collected real photographs (not cartoons or drawings) that sample a broad range of image types, from landscapes to photos of people and pets.
To identify factors—from lines to eye-like shapes—that contribute to the memorability of an image, Needell and Bainbridge used “residual neural networks,” a technique in artificial intelligence for teasing apart some of the components of memorability that might not be apparent to the human eye.