Identifying Dominant People in Meetings from Audio-Visual Sensors

This paper provides an overview of the area of automated dominance estimation in group meetings. We describe research in social psychology and use this to explain the motivations behind suggested automated systems. With the growth in availability of conversational data captured in meeting rooms, it is possible to investigate how multi-sensor data allows us to characterize non-verbal behaviors that contribute towards dominance. We use an overview of our own work to address the challenges and opportunities in this area of research.