Analyzing Group Interactions in Conversations: a Review
noindent Multiparty face-to-face conversations in professional and social settings represent an emerging research domain for which automatic activity-based analysis is relevant for scientific and practical reasons. The activity patterns emerging from groups engaged in conversations are intrinsically multimodal and thus constitute interesting target problems for multistream and multisensor fusion techniques. In this paper, a summarized review of the literature on automatic analysis of group activities in face-to-face conversational settings is presented. A basic categorization of group activities is proposed based on their typical temporal scale, and existing works are then discussed for various types of activities and trends including addressing, turn taking, interest, and dominance.
Published in Proc. IEEE Int. Conf. on Multisensor Fusion and Integration for Intelligent Systems (MFI), Special Session on Multisensor Fusion for Human-Activity Analysis, invited paper, Heidelberg, Sep. 2006.
Record created on 2010-02-11, modified on 2016-08-08