Capturing Interactions in Meetings with Omnidirectional Cameras

Human interaction is one of the most important characteristics of meetings. To explore complex human interactions in meetings we must understand them and their components in detail. In this paper we present our efforts in capturing human interactions in meetings using omnidirectional cameras. We present algorithms for person tracking, head pose estimation, and face recognition from omnidirectional images. We also discuss an approach for the estimation of who was talking to whom based on tracked head poses of the participants. Finally, we address the problem of activity modeling based on moving trajectories of people in a meeting room. We report experimental results to demonstrate the feasibility of the presented technologies and discuss future work.