Follow the Eyes: Head-Mounted Cameras Could Help Robots Understand Social Interactions

What is everyone looking at? It’s a common question in social settings because the answer identifies something of interest, or helps delineate social groupings. Those insights someday will be essential for robots designed to interact with humans, so researchers at Carnegie Mellon University’s Robotics Institute have developed a method for detecting where people’s gazes intersect.

The researchers tested the method using groups of people with head-mounted video cameras. By noting where their gazes converged in three-dimensional space, the researchers could determine if they were listening to a single speaker, interacting as a group, or even following the bouncing ball in a ping-pong game.

The system thus uses crowdsourcing to provide subjective information about social groups that would otherwise be difficult or impossible for a robot to ascertain.

The researchers’ algorithm for determining “social saliency” could ultimately be used to evaluate a variety of social cues, such as the expressions on people’s faces or body movements, or data from other types of visual or audio sensors.

"This really is just a first step toward analyzing the social signals of people," said Hyun Soo Park, a Ph.D. student in mechanical engineering, who worked on the project with Yaser Sheikh, assistant research professor of robotics, and Eakta Jain of Texas Instruments, who was awarded a Ph.D. in robotics last spring. "In the future, robots will need to interact organically with people and to do so they must understand their social environment, not just their physical environment."