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 [BibTeX] [Marc21]
Automatic Analysis of Multimodal Group Actions in Meetings
Type of publication: Journal paper
Citation: mccowan-rr-03-27b
Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence (to appear)
Year: 2004
Note: To appear.
Crossref: mccowan-rr-03-27:
Abstract: This paper investigates the recognition of group actions in meetings. A statistical framework is proposed in which group actions result from the interactions of the individual participants. The group actions are modelled using different HMM-based approaches, where the observations are provided by a set of audio-visual features monitoring the actions of individuals. Experiments demonstrate the importance of taking interactions into account in modelling 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.
Userfields: ipdmembership={speech, learning, vision}, language={English},
Keywords:
Projects Idiap
Authors McCowan, Iain A.
Gatica-Perez, Daniel
Bengio, Samy
Lathoud, Guillaume
Barnard, Mark
Zhang, Dong
Added by: [UNK]
Total mark: 0
Attachments
  • mccowan-03-27.pdf
  • mccowan-03-27.ps.gz
Notes