logo Idiap Research Institute        
 [BibTeX] [Marc21]
Multimodal Integration for Meeting Group Action Segmentation and Recognition
Type of publication: Conference paper
Citation: zhang-rr-05-31b
Booktitle: MLMI
Year: 2005
Note: IDIAP-RR 05-31
Crossref: zhang-rr-05-31:
Abstract: We address the problem of segmentation and recognition of sequences of multimodal human interactions in meetings. These interactions can be seen as a rough structure of a meeting, and can be used either as input for a meeting browser or as a first step towards a higher semantic analysis of the meeting. A common lexicon of multimodal group meeting actions, a shared meeting data set, and a common evaluation procedure enable us to compare the different approaches. We compare three different multimodal feature sets and four modelling infrastructures: a higher semantic feature approach, multi-layer HMMs, a multi-stream DBN, as well as a multi-stream mixed-state DBN for disturbed data.
Userfields: ipdmembership={vision},
Projects Idiap
Authors Al-Hames, Marc
Dielmann, Alfred
Gatica-Perez, Daniel
Reiter, Stephan
Renals, Steve
Zhang, Dong
Added by: [UNK]
Total mark: 0
  • mlmi-05-joint.pdf
  • rr-05-31.ps.gz