Peripheral Vision for Machines

Beyond robotics

The Benefits of Peripheral Vision for Machines

Researchers find similarities between how some computer-vision systems process images and how humans see out of the corners of our eyes.

Adam Zewe | MIT News Office

Publication Date:March 2, 2022

Perhaps computer vision and human vision have more in common than meets the eye?

Research from MIT suggests that a certain type of robust computer-vision model perceives visual representations similarly to the way humans do using peripheral vision. These models, known as adversarially robust models, are designed to overcome subtle bits of noise that have been added to image data.

The way these models learn to transform images is similar to some elements involved in human peripheral processing, the researchers found. But because machines do not have a visual periphery, little work on computer vision models has focused on peripheral processing, says senior author Arturo Deza, a postdoc in the Center for Brains, Minds, and Machines.

“It seems like peripheral vision, and the textural representations that are going on there, have been shown to be pretty useful for human vision. So, our thought was, OK, maybe there might be some uses in machines, too,” says lead author Anne Harrington, a graduate student in the Department of Electrical Engineering and Computer Science.

The results suggest that designing a machine-learning model to include some form of peripheral processing could enable the model to automatically learn visual representations that are robust to some subtle manipulations in image data. This work could also help shed some light on the goals of peripheral processing in humans, which are still not well-understood, Deza adds.  ... '