Inferring a User's Intent on Joining or Passing by Social Groups

Abstract

Modeling the interactions between users and social groups of virtual agents (VAs) is vital in many virtual-reality-based applications. However, only little research on group encounters has been conducted yet. We intend to close this gap by focusing on the distinction between joining and passing-by a group. To enhance the interactive capacity of VAs in these situations, knowing the user's objective is required to show reasonable reactions. To this end, we propose a classification scheme which infers the user's intent based on social cues such as proxemics, gazing and orientation, followed by triggering believable, non-verbal actions on the VAs. We tested our approach in a pilot study with overall promising results and discuss possible improvements for further studies.