title: Automatic analysis of multimodal group actions in meetings.
abstract: This paper investigates the recognition of group actions in meetings. A framework is employed in which group actions result from the interactions of the individual participants. The group actions are modeled using different HMM-based approaches, where the observations are provided by a set of audiovisual features monitoring the actions of individuals. Experiments demonstrate the importance of taking interactions into account in modeling the group actions. It is also shown that the visual modality contains useful information, even for predominantly audio-based events, motivating a multimodal approach to meeting analysis.
authors.affiliation: IDIAP Research Institute, Rue du Simplon 4, CP 592, CH-1920 Martigny, Switzerland. mccowan@idiap.ch
authors.forename: Iain
authors.initials: I
authors.lastname: McCowan
authors.forename: Daniel
authors.initials: D
authors.lastname: Gatica-Perez
authors.forename: Samy
authors.initials: S
authors.lastname: Bengio
authors.forename: Guillaume
authors.initials: G
authors.lastname: Lathoud
authors.forename: Mark
authors.initials: M
authors.lastname: Barnard
authors.forename: Dong
authors.initials: D
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001525:Behavioral Sciences / Q000379:methods*; D016000:Cluster Analysis; D003198:Computer Simulation; D006126:Group Processes; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012919:Social Behavior