MIT alogrithm can predict photo memorability at "near-human" levels.
Scientists have created an algorithm that can make your photographs more captivating and memorable.
How To: Buy a Pokemon Go Plus
Massachusetts Institute of Technology researchers have designed an algorithm that can predict memorability of a photograph at near-human levels, meaning it can tell which faces, scenes and objects in photographs are more likely to be remembered by humans.
“Understanding memorability can help us make systems to capture the most important information, or, conversely, to store information that humans will most likely forget,” said Aditya Khosla, lead author of the study. “It’s like having an instant focus group that tells you how likely it is that someone will remember a visual message.”
But how does this algorithm actually work? When a photograph is uploaded to the algorithm called “MemNet”, it creates a heat map which signifies exactly which parts of image are most memorable.
Researchers have incorporated techniques from deep-learning (DL) into it. DL is a branch of machine learning that can teach computers how to sift through massive amount of data and to find patterns all on their own. Such techniques are already involved in Google search and Facebook’s photo tagging. But it’s the first time when these techniques are used in computers for predicting what will be memorable for humans.
“While deep-learning has propelled much progress in object recognition and scene understanding, predicting human memory has often been viewed as a higher-level cognitive process that computer scientists will never be able to tackle,” said co-author Aude Oliva from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) . “Well, we can, and we did!”
Researchers fed their algorithm tens of thousands of images from several different databases. Each image received a “memorability score” based on the ability of humans would remember them. The algorithm processes data without human guidance and continues to readjust its function and produce more accurate predictions as it receives more data.
In experiments, MemNet algorithm performed 30% better than existing algorithms and was found almost as accurate as humans are.
The research also shed light on the nature of human’s memory and how their memory can be improved if they view more memorable images.
“This sort of research gives us a better understanding of the visual information that people pay attention to,” said Alexei Efros an associate professor at University of California, Berkeley. “For marketers, movie-makers and other content creators, being able to model your mental state as you look at something is an exciting new direction to explore.”
Don't Miss: Nintendo Switch: Everything You Need To Know
The next thing will be, researchers are planning to turn it into an app which will allow fine adjustments in the photographs and will make them more memorable.