Researchers at Carnegie Mellon University’s Robotics Institute have developed a method for detecting where people’s gazes intersect. 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, feels the researchers.
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 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.
The researchers say they were surprised by the level of detail they were able to detect. In the party setting, for instance, the algorithm didn’t just indicate that people were looking at the ping-pong table; the gaze concurrence video actually shows the flight of the ball as it bounces and is batted back and forth.
That finding suggests another possible application for monitoring gaze concurrence: player-level views of ball games. If basketball players all wore head-mounted cameras, for instance, it might be possible to reconstruct the game, not from the point of view of a single player, but from a collective view of the players as they all keep their eyes on the ball.
Another potential use is the study of social behavior, such as group dynamics and gender interactions, and research into behavioral disorders, such as autism.
The research was sponsored by the Samsung Global Research Outreach Program, Intel and the National Science Foundation.