Detecting States of Mind Through Non-verbal Behavior Using the Microsoft Kinect
Led by Prof. Jeremy Bailenson, Department of Communication
What if we could automatically detect how well members of a group are “synching” on a collaborative project?
This project sought to identify data-driven indicators that can detect how well a group is “syncing” on a collaborative project. The study used inexpensive commercial videogame platforms to assess non-verbal behavior. It also used computational methods to predict collaborative innovation in learning and creative tasks. The research team developed a “thin slice” approach to non-verbal behavior data analysis. They examined face-to-face and online collaboration in dyads in order to help managers predict future success of creative work teams.
“Given that the production and perception of nonverbal behavior may have cross-cultural elements, finding ways to automatically detect and measure nonverbal behaviors based on body movements will continue to be an important area of future work.”
Prof. Jeremy Bailenson, Department of Communication, Virtual Human Interaction Lab.
Jeremy Bailenson, Andrea Stevenson Won, Wenqing Dai and Le Yu
View Project Summary
View Project Report
More From Jeremy:
Presentation from the mediaX 2014 Conference.
Engage and Dive Deeper into one of Jeremy Bailenson's presentations with this INTERACTIVE VIDEO.