Identifying the Focus of Attention in Human-Robot Conversational Groups

We propose a method for detecting the group's focus of attention: the visual point at which a majority of participants direct their gaze in a conversation. This information enables a robot to infer important conversational cues and adjust its behavior to support more natural conversational interactions. Our approach uses a Hidden Markov Model based on mimicry, where the robot observes the head orientation of participants and infers their gaze direction to identify the group's focus of attention. We demonstrate our method by replicating the gaze patterns of the group members, showing that the robot can accurately determine the focal point. We evaluated our algorithm using a combination of datasets and real-world scenarios with a Fetch robot, demonstrating an accuracy of 81% compared to a baseline of 54%. Our proposed method has the potential to significantly improve group-oriented human-robot interaction.