Measuring Visual Social Engagement from Proxemics and Gaze.

When we approach a group, there is an exchange of a multitude of verbal or non-verbal social signals to indicate that we are looking to interact. We continue to share these signals throughout the interaction to portray our thoughts and motivations. We define an interaction by the signals we send; sending different signals evokes a different response. Giving social robots the knowledge of group social interaction, they will have the ability to more effectively participate in these interactions in the real world. In this paper, we present the results from an online data collection study looking at social group dynamics. We collected a dataset of social behaviours in a group using a socially interactive game played online by 88 participants. We also introduce a novel visual social engagement metric, which is derived from two social signals: proxemics (distance between interaction participants) and mutual gaze. We propose a mathematical formula of both mutual gaze as the product of the mutual distances to the optical axis, and the visual social engagement as mutual gaze divided by distance between participants. Additionally, we investigate the influence of personality traits on the resulting interaction patterns. Using the metric, we create unique interaction profiles which suggest that participants have an interaction 'style'. No clear correlation between personality and interaction patterns was found.